Sr. Staff AI Engineer At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Define and steer the technical AI architecture vision, integrating applied research breakthroughs into production ecosystems with reliability and scale Lead the establishment of AI performance, safety, and transparency standards that guide all model development and deployment company-wide Drive multi-year platform initiatives that unify data, compute and model lifecycle management under and cohesive enterprise AI architecture Mentor senior technical leaders across research, data and engineering disciplines, developing the next generation of Capital One's AI technical leadership Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 10 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies At least 10 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience architecting AI platforms with tradeoff decisions around cost, latency, throughput and accuracy 9 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the SVP level Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Recognized industry leader in applied AI or machine learning infrastructure through patents, publications, or open-source leadership Demonstrated experience designing long-term AI infrastructure strategies - balancing cost, scale, ethics and regulatory compliance Experience driving organization-wide adoption of AI safety, alignment and governance standards, collaborating with policy, risk and legal teams Proven ability to shape R&D investment strategy by identifying breakthrough AI capabilities with material business impact Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $314,800 - $359,300 for Sr. Staff AI Engineer McLean, VA: $314,800 - $359,300 for Sr. Staff AI Engineer New York, NY: $343,400 - $392,000 for Sr. Staff AI Engineer Richmond, VA: $286,200 - $326,700 for Sr. Staff AI Engineer San Francisco, CA: $343,400 - $392,000 for Sr. Staff AI Engineer San Jose, CA: $343,400 - $392,000 for Sr. Staff AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
09/23/2026
Full time
Sr. Staff AI Engineer At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Define and steer the technical AI architecture vision, integrating applied research breakthroughs into production ecosystems with reliability and scale Lead the establishment of AI performance, safety, and transparency standards that guide all model development and deployment company-wide Drive multi-year platform initiatives that unify data, compute and model lifecycle management under and cohesive enterprise AI architecture Mentor senior technical leaders across research, data and engineering disciplines, developing the next generation of Capital One's AI technical leadership Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 10 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies At least 10 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience architecting AI platforms with tradeoff decisions around cost, latency, throughput and accuracy 9 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the SVP level Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Recognized industry leader in applied AI or machine learning infrastructure through patents, publications, or open-source leadership Demonstrated experience designing long-term AI infrastructure strategies - balancing cost, scale, ethics and regulatory compliance Experience driving organization-wide adoption of AI safety, alignment and governance standards, collaborating with policy, risk and legal teams Proven ability to shape R&D investment strategy by identifying breakthrough AI capabilities with material business impact Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $314,800 - $359,300 for Sr. Staff AI Engineer McLean, VA: $314,800 - $359,300 for Sr. Staff AI Engineer New York, NY: $343,400 - $392,000 for Sr. Staff AI Engineer Richmond, VA: $286,200 - $326,700 for Sr. Staff AI Engineer San Francisco, CA: $343,400 - $392,000 for Sr. Staff AI Engineer San Jose, CA: $343,400 - $392,000 for Sr. Staff AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Sr. Staff AI Engineer At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Define and steer the technical AI architecture vision, integrating applied research breakthroughs into production ecosystems with reliability and scale Lead the establishment of AI performance, safety, and transparency standards that guide all model development and deployment company-wide Drive multi-year platform initiatives that unify data, compute and model lifecycle management under and cohesive enterprise AI architecture Mentor senior technical leaders across research, data and engineering disciplines, developing the next generation of Capital One's AI technical leadership Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 10 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies At least 10 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience architecting AI platforms with tradeoff decisions around cost, latency, throughput and accuracy 9 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the SVP level Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Recognized industry leader in applied AI or machine learning infrastructure through patents, publications, or open-source leadership Demonstrated experience designing long-term AI infrastructure strategies - balancing cost, scale, ethics and regulatory compliance Experience driving organization-wide adoption of AI safety, alignment and governance standards, collaborating with policy, risk and legal teams Proven ability to shape R&D investment strategy by identifying breakthrough AI capabilities with material business impact Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $314,800 - $359,300 for Sr. Staff AI Engineer McLean, VA: $314,800 - $359,300 for Sr. Staff AI Engineer New York, NY: $343,400 - $392,000 for Sr. Staff AI Engineer Richmond, VA: $286,200 - $326,700 for Sr. Staff AI Engineer San Francisco, CA: $343,400 - $392,000 for Sr. Staff AI Engineer San Jose, CA: $343,400 - $392,000 for Sr. Staff AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
09/23/2026
Full time
Sr. Staff AI Engineer At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Define and steer the technical AI architecture vision, integrating applied research breakthroughs into production ecosystems with reliability and scale Lead the establishment of AI performance, safety, and transparency standards that guide all model development and deployment company-wide Drive multi-year platform initiatives that unify data, compute and model lifecycle management under and cohesive enterprise AI architecture Mentor senior technical leaders across research, data and engineering disciplines, developing the next generation of Capital One's AI technical leadership Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 10 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies At least 10 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience architecting AI platforms with tradeoff decisions around cost, latency, throughput and accuracy 9 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the SVP level Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Recognized industry leader in applied AI or machine learning infrastructure through patents, publications, or open-source leadership Demonstrated experience designing long-term AI infrastructure strategies - balancing cost, scale, ethics and regulatory compliance Experience driving organization-wide adoption of AI safety, alignment and governance standards, collaborating with policy, risk and legal teams Proven ability to shape R&D investment strategy by identifying breakthrough AI capabilities with material business impact Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $314,800 - $359,300 for Sr. Staff AI Engineer McLean, VA: $314,800 - $359,300 for Sr. Staff AI Engineer New York, NY: $343,400 - $392,000 for Sr. Staff AI Engineer Richmond, VA: $286,200 - $326,700 for Sr. Staff AI Engineer San Francisco, CA: $343,400 - $392,000 for Sr. Staff AI Engineer San Jose, CA: $343,400 - $392,000 for Sr. Staff AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Sr. Staff AI Engineer At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Define and steer the technical AI architecture vision, integrating applied research breakthroughs into production ecosystems with reliability and scale Lead the establishment of AI performance, safety, and transparency standards that guide all model development and deployment company-wide Drive multi-year platform initiatives that unify data, compute and model lifecycle management under and cohesive enterprise AI architecture Mentor senior technical leaders across research, data and engineering disciplines, developing the next generation of Capital One's AI technical leadership Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 10 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies At least 10 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience architecting AI platforms with tradeoff decisions around cost, latency, throughput and accuracy 9 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the SVP level Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Recognized industry leader in applied AI or machine learning infrastructure through patents, publications, or open-source leadership Demonstrated experience designing long-term AI infrastructure strategies - balancing cost, scale, ethics and regulatory compliance Experience driving organization-wide adoption of AI safety, alignment and governance standards, collaborating with policy, risk and legal teams Proven ability to shape R&D investment strategy by identifying breakthrough AI capabilities with material business impact Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $314,800 - $359,300 for Sr. Staff AI Engineer McLean, VA: $314,800 - $359,300 for Sr. Staff AI Engineer New York, NY: $343,400 - $392,000 for Sr. Staff AI Engineer Richmond, VA: $286,200 - $326,700 for Sr. Staff AI Engineer San Francisco, CA: $343,400 - $392,000 for Sr. Staff AI Engineer San Jose, CA: $343,400 - $392,000 for Sr. Staff AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
09/23/2026
Full time
Sr. Staff AI Engineer At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Define and steer the technical AI architecture vision, integrating applied research breakthroughs into production ecosystems with reliability and scale Lead the establishment of AI performance, safety, and transparency standards that guide all model development and deployment company-wide Drive multi-year platform initiatives that unify data, compute and model lifecycle management under and cohesive enterprise AI architecture Mentor senior technical leaders across research, data and engineering disciplines, developing the next generation of Capital One's AI technical leadership Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 10 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies At least 10 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience architecting AI platforms with tradeoff decisions around cost, latency, throughput and accuracy 9 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the SVP level Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Recognized industry leader in applied AI or machine learning infrastructure through patents, publications, or open-source leadership Demonstrated experience designing long-term AI infrastructure strategies - balancing cost, scale, ethics and regulatory compliance Experience driving organization-wide adoption of AI safety, alignment and governance standards, collaborating with policy, risk and legal teams Proven ability to shape R&D investment strategy by identifying breakthrough AI capabilities with material business impact Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $314,800 - $359,300 for Sr. Staff AI Engineer McLean, VA: $314,800 - $359,300 for Sr. Staff AI Engineer New York, NY: $343,400 - $392,000 for Sr. Staff AI Engineer Richmond, VA: $286,200 - $326,700 for Sr. Staff AI Engineer San Francisco, CA: $343,400 - $392,000 for Sr. Staff AI Engineer San Jose, CA: $343,400 - $392,000 for Sr. Staff AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Job DescriptionJob Description MKS2 Technologies, LLC, an award-winning high growth small business, creates innovative and customer-centric technology solutions in the areas of Cyber Security, Instructional Design and Training, Software Engineering and IT Support Services to improve the security and well-being of our clients. Our commitment to excellence and our "Mission First" orientation has resulted in steady growth and an expanding client base across government agencies. We have employees nationwide and for the past three consecutive years were named one of the fastest growing Veteran-owned companies in the nation. Please take a moment to browse through our website and learn more about what it means to serve with MKS2. Senior Microsoft Windows Field Deployment Technician Salary: $65,000 - $70,000 annually with full benefits As a Senior Microsoft Windows Field Deployment Technician on our project, you'll work with a team of onsite technicians supporting the VA's EHR deployment and training project and assist with oversight of workload. In this role you will be deploying, imaging, and setting up equipment (PCs, Laptops, Docking Stations, Monitors, Printers, Scanners, and Network Connections) around the VA medical center campus as well as offsite training centers. This role combines strong technical skills with an emphasis on delivering a high level of customer service. You will be responsible for unboxing, setting up, installing, configuring, removing equipment, re-packaging hardware for shipment, and with limited supervision. This role will also require setup of equipment at various training sites, verifying each computer has the most current VA computer image, computer is available for scheduled security scans and updates, Active Directory assignment for training use, configure network connectivity in the training room, and computer peripherals are installed at each training seat. You will be managing inventory and network connectivity at each training site and ensuring connectivity during all training sessions. This position is located onsite at Veterans' Administration Medical Centers and offsite training locations with daytime hours and may require evening hours and the potential for weekend hours. The staff may be required to travel to other sites outside of the metropolitan area throughout the week. You Have: 5 years' experience in imaging, installing computer equipment, and managing teams of technical staff Must be able to unpack/re-pack, move, and install pallets of IT equipment, with each item weighing up to 50 pounds, with no restrictions Must have personal transportation available during work hours Will need to consistently traverse around the site campus, transporting equipment to various office buildings, and frequently stoop, crouch, and reach to set up/remove computers/pull cords under desks and in server closets Will frequently need to be able to push carts carrying equipment Experience with hardware and software support, troubleshooting, system imaging, hardware break-fix support (i.e., laptops, desktops, and printers), refresh, upgrade, and deployment projects, as well as excellent customer service skills Experience with conducting routine system administration tasks and logging data in system admin logs Experience with maintaining and troubleshooting a wide variety of systems and networks, including high-availability systems Knowledge of debugging protocols and processes, and the ability to work independently while providing excellent customer service Bachelor's degree in computer science, Information Systems, Information Technology, or equivalent, and 5 total years of experience; or 13 total years of experience in lieu of a degree Nice If You Have: Experience with the ServiceNow ticketing system a plus Experience with the VA Public Trust clearance Experience with Microsoft windows desktop deployments Experience as IT helpdesk Tier 1 or 2 Diversity creates a healthier atmosphere: MKS2 Technologies is proud to be an Equal Employment Opportunity / Affirmative Action employer, and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, age, national origin, protected veteran status, disability status, sexual orientation, gender identity or expression, marital status, genetic information, or any other characteristic protected by law.
09/23/2026
Full time
Job DescriptionJob Description MKS2 Technologies, LLC, an award-winning high growth small business, creates innovative and customer-centric technology solutions in the areas of Cyber Security, Instructional Design and Training, Software Engineering and IT Support Services to improve the security and well-being of our clients. Our commitment to excellence and our "Mission First" orientation has resulted in steady growth and an expanding client base across government agencies. We have employees nationwide and for the past three consecutive years were named one of the fastest growing Veteran-owned companies in the nation. Please take a moment to browse through our website and learn more about what it means to serve with MKS2. Senior Microsoft Windows Field Deployment Technician Salary: $65,000 - $70,000 annually with full benefits As a Senior Microsoft Windows Field Deployment Technician on our project, you'll work with a team of onsite technicians supporting the VA's EHR deployment and training project and assist with oversight of workload. In this role you will be deploying, imaging, and setting up equipment (PCs, Laptops, Docking Stations, Monitors, Printers, Scanners, and Network Connections) around the VA medical center campus as well as offsite training centers. This role combines strong technical skills with an emphasis on delivering a high level of customer service. You will be responsible for unboxing, setting up, installing, configuring, removing equipment, re-packaging hardware for shipment, and with limited supervision. This role will also require setup of equipment at various training sites, verifying each computer has the most current VA computer image, computer is available for scheduled security scans and updates, Active Directory assignment for training use, configure network connectivity in the training room, and computer peripherals are installed at each training seat. You will be managing inventory and network connectivity at each training site and ensuring connectivity during all training sessions. This position is located onsite at Veterans' Administration Medical Centers and offsite training locations with daytime hours and may require evening hours and the potential for weekend hours. The staff may be required to travel to other sites outside of the metropolitan area throughout the week. You Have: 5 years' experience in imaging, installing computer equipment, and managing teams of technical staff Must be able to unpack/re-pack, move, and install pallets of IT equipment, with each item weighing up to 50 pounds, with no restrictions Must have personal transportation available during work hours Will need to consistently traverse around the site campus, transporting equipment to various office buildings, and frequently stoop, crouch, and reach to set up/remove computers/pull cords under desks and in server closets Will frequently need to be able to push carts carrying equipment Experience with hardware and software support, troubleshooting, system imaging, hardware break-fix support (i.e., laptops, desktops, and printers), refresh, upgrade, and deployment projects, as well as excellent customer service skills Experience with conducting routine system administration tasks and logging data in system admin logs Experience with maintaining and troubleshooting a wide variety of systems and networks, including high-availability systems Knowledge of debugging protocols and processes, and the ability to work independently while providing excellent customer service Bachelor's degree in computer science, Information Systems, Information Technology, or equivalent, and 5 total years of experience; or 13 total years of experience in lieu of a degree Nice If You Have: Experience with the ServiceNow ticketing system a plus Experience with the VA Public Trust clearance Experience with Microsoft windows desktop deployments Experience as IT helpdesk Tier 1 or 2 Diversity creates a healthier atmosphere: MKS2 Technologies is proud to be an Equal Employment Opportunity / Affirmative Action employer, and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, age, national origin, protected veteran status, disability status, sexual orientation, gender identity or expression, marital status, genetic information, or any other characteristic protected by law.
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The World's Most Experienced Driver -to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. The Simulator Team at Waymo builds state-of-the-art simulations of realistic environments for testing, training, and validation of the Waymo Driver. Our team is a diverse, and collaborative group of machine learning (ML) engineers, software engineers, and ML research engineers. We develop industry-leading simulation solutions using advanced generative and reconstructive ML algorithms, to model the real world, encompassing realistic agents, roads, traffic systems, weather, and the full sensor suite (Camera, Lidar, Radar). To accelerate the fidelity, scalability, controllability, and richness of our simulations, we are pushing the frontiers of 3D world modeling. We leverage state-of-the-art ML technologies trained on large-scale datasets to create dynamic and semantically rich virtual worlds, directly impacting the development and validation of the Waymo Driver. In this role, you will report to a Senior Staff Engineering Manager. You will: Lead the design, development and deployment of cutting-edge 4D world models and generative systems for ultra-realistic and controllable sensor and semantics generation for simulation use cases at waymo. Architect and implement scalable and robust ML pipelines for training, evaluating, and deploying large-scale generative models into our simulation infrastructure, including techniques like model distillation and quantization. Build and scale production-ready video generation techniques (e.g., Diffusion, Flow Matching) to create dynamic and interactive simulation environments. Apply Vision Language Models (VLMs) to enhance the semantic understanding and controllability of our world simulation products. Partner with world class research teams across Waymo and Alphabet to leverage State-of-The-Art research in 4D world modeling and generative AI into robust, production-ready solutions. Mentor and provide technical guidance to other engineers on the team. You have: MS or PhD in Computer Science, Machine Learning, Robotics, or a related field. 5+ years of experience in ML engineering and applied Deep Learning, with a strong portfolio of shipped products or publication record. Proven experience in developing and training large-scale generative models for video generation (e.g., Diffusion models, Flow Matching) or Vision Language Models (VLMs) and their applications. Deep expertise in 3D World Modeling or 3D computer vision. Familiarity with 3D reconstruction and rendering techniques (e.g., 3D Gaussian Splatting). Strong programming skills in Python and experience with ML frameworks such as Jax/Flax, PyTorch or Tensorflow. We prefer: PhD and a strong track record of delivering impactful ML products in 3D generative models, world models, or video generation Experience in simulating sensor data (Camera, Lidar, Radar) and/or semantic scenes. Experience with autonomous systems, robotics, or autonomous vehicle simulation. Experience in training and optimizing large scale models on GPU/TPU clusters for efficient serving. Experience in C++ for production systems. The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $213,000-$263,000 USD
09/23/2026
Full time
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The World's Most Experienced Driver -to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. The Simulator Team at Waymo builds state-of-the-art simulations of realistic environments for testing, training, and validation of the Waymo Driver. Our team is a diverse, and collaborative group of machine learning (ML) engineers, software engineers, and ML research engineers. We develop industry-leading simulation solutions using advanced generative and reconstructive ML algorithms, to model the real world, encompassing realistic agents, roads, traffic systems, weather, and the full sensor suite (Camera, Lidar, Radar). To accelerate the fidelity, scalability, controllability, and richness of our simulations, we are pushing the frontiers of 3D world modeling. We leverage state-of-the-art ML technologies trained on large-scale datasets to create dynamic and semantically rich virtual worlds, directly impacting the development and validation of the Waymo Driver. In this role, you will report to a Senior Staff Engineering Manager. You will: Lead the design, development and deployment of cutting-edge 4D world models and generative systems for ultra-realistic and controllable sensor and semantics generation for simulation use cases at waymo. Architect and implement scalable and robust ML pipelines for training, evaluating, and deploying large-scale generative models into our simulation infrastructure, including techniques like model distillation and quantization. Build and scale production-ready video generation techniques (e.g., Diffusion, Flow Matching) to create dynamic and interactive simulation environments. Apply Vision Language Models (VLMs) to enhance the semantic understanding and controllability of our world simulation products. Partner with world class research teams across Waymo and Alphabet to leverage State-of-The-Art research in 4D world modeling and generative AI into robust, production-ready solutions. Mentor and provide technical guidance to other engineers on the team. You have: MS or PhD in Computer Science, Machine Learning, Robotics, or a related field. 5+ years of experience in ML engineering and applied Deep Learning, with a strong portfolio of shipped products or publication record. Proven experience in developing and training large-scale generative models for video generation (e.g., Diffusion models, Flow Matching) or Vision Language Models (VLMs) and their applications. Deep expertise in 3D World Modeling or 3D computer vision. Familiarity with 3D reconstruction and rendering techniques (e.g., 3D Gaussian Splatting). Strong programming skills in Python and experience with ML frameworks such as Jax/Flax, PyTorch or Tensorflow. We prefer: PhD and a strong track record of delivering impactful ML products in 3D generative models, world models, or video generation Experience in simulating sensor data (Camera, Lidar, Radar) and/or semantic scenes. Experience with autonomous systems, robotics, or autonomous vehicle simulation. Experience in training and optimizing large scale models on GPU/TPU clusters for efficient serving. Experience in C++ for production systems. The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $213,000-$263,000 USD
Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. Tenstorrent is seeking talented Physical Design Engineers to implement high-performance blocks for our industry-leading CPU and AI/ML architectures. You'll own the complete implementation flow from synthesis to tapeout, working alongside world-class engineers to push the boundaries of performance, power, and area. If you're passionate about crafting silicon that powers the future of AI computing and thrive on solving complex design challenges, we want you on our team. This role is hybrid , based out of Austin, TX, Santa Clara, CA or Fort Collins, CO. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are A hands-on engineer with deep expertise in SOC/ASIC physical design and a track record of successful tapeouts. Passionate about optimizing PPA through innovative implementation techniques and close RTL collaboration. Strong problem solver who excels at debugging complex issues across design hierarchies. Collaborative team player who thrives in fast-paced, technically challenging environments. What We Need BS/MS/PhD in EE/ECE/CE/CS with proven experience in synthesis, PnR, and timing closure on taped-out designs. Expertise with industry-standard tools (Innovus, PrimeTime, RedHawk) and scripting languages (Tcl, Perl, Python). Deep understanding of advanced node challenges and low-power design techniques (power gating, multi-Vt, voltage scaling). Experience driving physical design requirements from early architecture through final signoff. What You Will Learn How to implement cutting-edge AI accelerators and high-performance CPUs on the most advanced process nodes. Innovative PPA optimization techniques and methodologies for next-generation chiplet architectures. End-to-end ownership from flow development to signoff in collaboration with architecture and IP teams. Direct impact on products that are redefining the landscape of AI and high-performance computing. Compensation for all engineers at Tenstorrent ranges from $100k - $500k including base and variable compensation targets. Experience, skills, education, background and location all impact the actual offer made. Tenstorrent offers a highly competitive compensation package and benefits, and we are an equal opportunity employer. This offer of employment is contingent upon the applicant being eligible to access U.S. export-controlled technology. Due to U.S. export laws, including those codified in the U.S. Export Administration Regulations (EAR), the Company is required to ensure compliance with these laws when transferring technology to nationals of certain countries (such as EAR Country Groups D:1, E1, and E2). These requirements apply to persons located in the U.S. and all countries outside the U.S. As the position offered will have direct and/or indirect access to information, systems, or technologies subject to these laws, the offer may be contingent upon your citizenship/permanent residency status or ability to obtain prior license approval from the U.S. Commerce Department or applicable federal agency. If employment is not possible due to U.S. export laws, any offer of employment will be rescinded.
09/23/2026
Full time
Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. Tenstorrent is seeking talented Physical Design Engineers to implement high-performance blocks for our industry-leading CPU and AI/ML architectures. You'll own the complete implementation flow from synthesis to tapeout, working alongside world-class engineers to push the boundaries of performance, power, and area. If you're passionate about crafting silicon that powers the future of AI computing and thrive on solving complex design challenges, we want you on our team. This role is hybrid , based out of Austin, TX, Santa Clara, CA or Fort Collins, CO. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are A hands-on engineer with deep expertise in SOC/ASIC physical design and a track record of successful tapeouts. Passionate about optimizing PPA through innovative implementation techniques and close RTL collaboration. Strong problem solver who excels at debugging complex issues across design hierarchies. Collaborative team player who thrives in fast-paced, technically challenging environments. What We Need BS/MS/PhD in EE/ECE/CE/CS with proven experience in synthesis, PnR, and timing closure on taped-out designs. Expertise with industry-standard tools (Innovus, PrimeTime, RedHawk) and scripting languages (Tcl, Perl, Python). Deep understanding of advanced node challenges and low-power design techniques (power gating, multi-Vt, voltage scaling). Experience driving physical design requirements from early architecture through final signoff. What You Will Learn How to implement cutting-edge AI accelerators and high-performance CPUs on the most advanced process nodes. Innovative PPA optimization techniques and methodologies for next-generation chiplet architectures. End-to-end ownership from flow development to signoff in collaboration with architecture and IP teams. Direct impact on products that are redefining the landscape of AI and high-performance computing. Compensation for all engineers at Tenstorrent ranges from $100k - $500k including base and variable compensation targets. Experience, skills, education, background and location all impact the actual offer made. Tenstorrent offers a highly competitive compensation package and benefits, and we are an equal opportunity employer. This offer of employment is contingent upon the applicant being eligible to access U.S. export-controlled technology. Due to U.S. export laws, including those codified in the U.S. Export Administration Regulations (EAR), the Company is required to ensure compliance with these laws when transferring technology to nationals of certain countries (such as EAR Country Groups D:1, E1, and E2). These requirements apply to persons located in the U.S. and all countries outside the U.S. As the position offered will have direct and/or indirect access to information, systems, or technologies subject to these laws, the offer may be contingent upon your citizenship/permanent residency status or ability to obtain prior license approval from the U.S. Commerce Department or applicable federal agency. If employment is not possible due to U.S. export laws, any offer of employment will be rescinded.
Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. Tenstorrent is seeking talented Physical Design Engineers to implement high-performance blocks for our industry-leading CPU and AI/ML architectures. You'll own the complete implementation flow from synthesis to tapeout, working alongside world-class engineers to push the boundaries of performance, power, and area. If you're passionate about crafting silicon that powers the future of AI computing and thrive on solving complex design challenges, we want you on our team. This role is hybrid , based out of Austin, TX, Santa Clara, CA or Fort Collins, CO. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are A hands-on engineer with deep expertise in SOC/ASIC physical design and a track record of successful tapeouts. Passionate about optimizing PPA through innovative implementation techniques and close RTL collaboration. Strong problem solver who excels at debugging complex issues across design hierarchies. Collaborative team player who thrives in fast-paced, technically challenging environments. What We Need BS/MS/PhD in EE/ECE/CE/CS with proven experience in synthesis, PnR, and timing closure on taped-out designs. Expertise with industry-standard tools (Innovus, PrimeTime, RedHawk) and scripting languages (Tcl, Perl, Python). Deep understanding of advanced node challenges and low-power design techniques (power gating, multi-Vt, voltage scaling). Experience driving physical design requirements from early architecture through final signoff. What You Will Learn How to implement cutting-edge AI accelerators and high-performance CPUs on the most advanced process nodes. Innovative PPA optimization techniques and methodologies for next-generation chiplet architectures. End-to-end ownership from flow development to signoff in collaboration with architecture and IP teams. Direct impact on products that are redefining the landscape of AI and high-performance computing. Compensation for all engineers at Tenstorrent ranges from $100k - $500k including base and variable compensation targets. Experience, skills, education, background and location all impact the actual offer made. Tenstorrent offers a highly competitive compensation package and benefits, and we are an equal opportunity employer. This offer of employment is contingent upon the applicant being eligible to access U.S. export-controlled technology. Due to U.S. export laws, including those codified in the U.S. Export Administration Regulations (EAR), the Company is required to ensure compliance with these laws when transferring technology to nationals of certain countries (such as EAR Country Groups D:1, E1, and E2). These requirements apply to persons located in the U.S. and all countries outside the U.S. As the position offered will have direct and/or indirect access to information, systems, or technologies subject to these laws, the offer may be contingent upon your citizenship/permanent residency status or ability to obtain prior license approval from the U.S. Commerce Department or applicable federal agency. If employment is not possible due to U.S. export laws, any offer of employment will be rescinded.
09/23/2026
Full time
Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. Tenstorrent is seeking talented Physical Design Engineers to implement high-performance blocks for our industry-leading CPU and AI/ML architectures. You'll own the complete implementation flow from synthesis to tapeout, working alongside world-class engineers to push the boundaries of performance, power, and area. If you're passionate about crafting silicon that powers the future of AI computing and thrive on solving complex design challenges, we want you on our team. This role is hybrid , based out of Austin, TX, Santa Clara, CA or Fort Collins, CO. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are A hands-on engineer with deep expertise in SOC/ASIC physical design and a track record of successful tapeouts. Passionate about optimizing PPA through innovative implementation techniques and close RTL collaboration. Strong problem solver who excels at debugging complex issues across design hierarchies. Collaborative team player who thrives in fast-paced, technically challenging environments. What We Need BS/MS/PhD in EE/ECE/CE/CS with proven experience in synthesis, PnR, and timing closure on taped-out designs. Expertise with industry-standard tools (Innovus, PrimeTime, RedHawk) and scripting languages (Tcl, Perl, Python). Deep understanding of advanced node challenges and low-power design techniques (power gating, multi-Vt, voltage scaling). Experience driving physical design requirements from early architecture through final signoff. What You Will Learn How to implement cutting-edge AI accelerators and high-performance CPUs on the most advanced process nodes. Innovative PPA optimization techniques and methodologies for next-generation chiplet architectures. End-to-end ownership from flow development to signoff in collaboration with architecture and IP teams. Direct impact on products that are redefining the landscape of AI and high-performance computing. Compensation for all engineers at Tenstorrent ranges from $100k - $500k including base and variable compensation targets. Experience, skills, education, background and location all impact the actual offer made. Tenstorrent offers a highly competitive compensation package and benefits, and we are an equal opportunity employer. This offer of employment is contingent upon the applicant being eligible to access U.S. export-controlled technology. Due to U.S. export laws, including those codified in the U.S. Export Administration Regulations (EAR), the Company is required to ensure compliance with these laws when transferring technology to nationals of certain countries (such as EAR Country Groups D:1, E1, and E2). These requirements apply to persons located in the U.S. and all countries outside the U.S. As the position offered will have direct and/or indirect access to information, systems, or technologies subject to these laws, the offer may be contingent upon your citizenship/permanent residency status or ability to obtain prior license approval from the U.S. Commerce Department or applicable federal agency. If employment is not possible due to U.S. export laws, any offer of employment will be rescinded.
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The World's Most Experienced Driver -to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. The Simulator Team at Waymo builds state-of-the-art simulations of realistic environments for testing and training the Waymo Driver. Your team will be a diverse, and collaborative group of machine learning (ML) engineers, software engineers and data scientists. We develop industry-leading simulation solutions using advanced ML algorithms that measure and enhance the performance of the Waymo Driver. We achieve those goals by jointly modeling the real world, including realistic agents (vehicles, pedestrians, cyclists, motorcyclists), roads, traffic control systems, and weather conditions, and the full sensor suite including camera, Lidar and radars. To increase the fidelity, scalability and controllability of our simulations,we employ the latest ML technologies such as large language models, foundational world models, and reconstructive methods trained on large-scale datasets with both generative and reconstructive technologies, as well as traditional rendering approaches. In this hybrid role, you will report to a Senior Staff Engineering Manager. You will: Work closely with onboard and research engineers to scale simulation and enable critical Waymo milestones Support development, testing and evolution of mapping data in the simulator Improve / monitor the performance, scalability and the reliability of the simulator Design the long term architecture to fit the product to an increasing number of internal customers You have: Hands-on experience building a popular (internal- or external-facing) product. Experience on backend knowledge such as workflows, databases, SQL, production monitoring, etc. Strong in C++. We prefer: Experience with the release of software in a highly distributed heterogeneous execution environment Experience with systems programming (game engines, database, OS, distributed) Experience with ML Previous TL experience The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $251,000-$310,000 USD
09/23/2026
Full time
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The World's Most Experienced Driver -to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. The Simulator Team at Waymo builds state-of-the-art simulations of realistic environments for testing and training the Waymo Driver. Your team will be a diverse, and collaborative group of machine learning (ML) engineers, software engineers and data scientists. We develop industry-leading simulation solutions using advanced ML algorithms that measure and enhance the performance of the Waymo Driver. We achieve those goals by jointly modeling the real world, including realistic agents (vehicles, pedestrians, cyclists, motorcyclists), roads, traffic control systems, and weather conditions, and the full sensor suite including camera, Lidar and radars. To increase the fidelity, scalability and controllability of our simulations,we employ the latest ML technologies such as large language models, foundational world models, and reconstructive methods trained on large-scale datasets with both generative and reconstructive technologies, as well as traditional rendering approaches. In this hybrid role, you will report to a Senior Staff Engineering Manager. You will: Work closely with onboard and research engineers to scale simulation and enable critical Waymo milestones Support development, testing and evolution of mapping data in the simulator Improve / monitor the performance, scalability and the reliability of the simulator Design the long term architecture to fit the product to an increasing number of internal customers You have: Hands-on experience building a popular (internal- or external-facing) product. Experience on backend knowledge such as workflows, databases, SQL, production monitoring, etc. Strong in C++. We prefer: Experience with the release of software in a highly distributed heterogeneous execution environment Experience with systems programming (game engines, database, OS, distributed) Experience with ML Previous TL experience The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $251,000-$310,000 USD
Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. Tenstorrent is seeking talented Physical Design Engineers to implement high-performance blocks for our industry-leading CPU and AI/ML architectures. You'll own the complete implementation flow from synthesis to tapeout, working alongside world-class engineers to push the boundaries of performance, power, and area. If you're passionate about crafting silicon that powers the future of AI computing and thrive on solving complex design challenges, we want you on our team. This role is hybrid , based out of Austin, TX, Santa Clara, CA or Fort Collins, CO. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are A hands-on engineer with deep expertise in SOC/ASIC physical design and a track record of successful tapeouts. Passionate about optimizing PPA through innovative implementation techniques and close RTL collaboration. Strong problem solver who excels at debugging complex issues across design hierarchies. Collaborative team player who thrives in fast-paced, technically challenging environments. What We Need BS/MS/PhD in EE/ECE/CE/CS with proven experience in synthesis, PnR, and timing closure on taped-out designs. Expertise with industry-standard tools (Innovus, PrimeTime, RedHawk) and scripting languages (Tcl, Perl, Python). Deep understanding of advanced node challenges and low-power design techniques (power gating, multi-Vt, voltage scaling). Experience driving physical design requirements from early architecture through final signoff. What You Will Learn How to implement cutting-edge AI accelerators and high-performance CPUs on the most advanced process nodes. Innovative PPA optimization techniques and methodologies for next-generation chiplet architectures. End-to-end ownership from flow development to signoff in collaboration with architecture and IP teams. Direct impact on products that are redefining the landscape of AI and high-performance computing. Compensation for all engineers at Tenstorrent ranges from $100k - $500k including base and variable compensation targets. Experience, skills, education, background and location all impact the actual offer made. Tenstorrent offers a highly competitive compensation package and benefits, and we are an equal opportunity employer. This offer of employment is contingent upon the applicant being eligible to access U.S. export-controlled technology. Due to U.S. export laws, including those codified in the U.S. Export Administration Regulations (EAR), the Company is required to ensure compliance with these laws when transferring technology to nationals of certain countries (such as EAR Country Groups D:1, E1, and E2). These requirements apply to persons located in the U.S. and all countries outside the U.S. As the position offered will have direct and/or indirect access to information, systems, or technologies subject to these laws, the offer may be contingent upon your citizenship/permanent residency status or ability to obtain prior license approval from the U.S. Commerce Department or applicable federal agency. If employment is not possible due to U.S. export laws, any offer of employment will be rescinded.
09/23/2026
Full time
Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. Tenstorrent is seeking talented Physical Design Engineers to implement high-performance blocks for our industry-leading CPU and AI/ML architectures. You'll own the complete implementation flow from synthesis to tapeout, working alongside world-class engineers to push the boundaries of performance, power, and area. If you're passionate about crafting silicon that powers the future of AI computing and thrive on solving complex design challenges, we want you on our team. This role is hybrid , based out of Austin, TX, Santa Clara, CA or Fort Collins, CO. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are A hands-on engineer with deep expertise in SOC/ASIC physical design and a track record of successful tapeouts. Passionate about optimizing PPA through innovative implementation techniques and close RTL collaboration. Strong problem solver who excels at debugging complex issues across design hierarchies. Collaborative team player who thrives in fast-paced, technically challenging environments. What We Need BS/MS/PhD in EE/ECE/CE/CS with proven experience in synthesis, PnR, and timing closure on taped-out designs. Expertise with industry-standard tools (Innovus, PrimeTime, RedHawk) and scripting languages (Tcl, Perl, Python). Deep understanding of advanced node challenges and low-power design techniques (power gating, multi-Vt, voltage scaling). Experience driving physical design requirements from early architecture through final signoff. What You Will Learn How to implement cutting-edge AI accelerators and high-performance CPUs on the most advanced process nodes. Innovative PPA optimization techniques and methodologies for next-generation chiplet architectures. End-to-end ownership from flow development to signoff in collaboration with architecture and IP teams. Direct impact on products that are redefining the landscape of AI and high-performance computing. Compensation for all engineers at Tenstorrent ranges from $100k - $500k including base and variable compensation targets. Experience, skills, education, background and location all impact the actual offer made. Tenstorrent offers a highly competitive compensation package and benefits, and we are an equal opportunity employer. This offer of employment is contingent upon the applicant being eligible to access U.S. export-controlled technology. Due to U.S. export laws, including those codified in the U.S. Export Administration Regulations (EAR), the Company is required to ensure compliance with these laws when transferring technology to nationals of certain countries (such as EAR Country Groups D:1, E1, and E2). These requirements apply to persons located in the U.S. and all countries outside the U.S. As the position offered will have direct and/or indirect access to information, systems, or technologies subject to these laws, the offer may be contingent upon your citizenship/permanent residency status or ability to obtain prior license approval from the U.S. Commerce Department or applicable federal agency. If employment is not possible due to U.S. export laws, any offer of employment will be rescinded.
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The World's Most Experienced Driver -to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. The ML Ops team, part of Waymo ML Platform team, builds tools and infrastructure to realize the ML flywheel at Waymo. This includes building automation and orchestration solutions to make complex ML workflows manageable and reliable. This team also partners closely with the modeling team to realize solutions to speed up developer velocity. We're looking for a software engineer to join the team to build and maintain the critical data and ML pipelines that powers ML development at Waymo. In this hybrid role, you will report to the Head of ML Platform- Senior Staff Software Engineer. You will: Develop Waymo's inference platform to make it scalable, high throughput, and low latency Work closely with other teams across Waymo in hosting both internal and external ML models, including LLMs Improving the efficiency of running inference on these large models to increase throughput and save cost Deploy and integrate model inference solutions across a variety of use cases, such as distillation, eval, dataset generation, active learning, and auto-labeling You have: 5+ years of professional experience in the field of software engineering Experience in programming C++ Experience with building highly scalable distributed system We prefer: Passionate about building internal infra and tools Experience with building model hosting and inference solutions Experience with handling datasets in the order of exabytes The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $213,000-$263,000 USD
09/23/2026
Full time
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The World's Most Experienced Driver -to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. The ML Ops team, part of Waymo ML Platform team, builds tools and infrastructure to realize the ML flywheel at Waymo. This includes building automation and orchestration solutions to make complex ML workflows manageable and reliable. This team also partners closely with the modeling team to realize solutions to speed up developer velocity. We're looking for a software engineer to join the team to build and maintain the critical data and ML pipelines that powers ML development at Waymo. In this hybrid role, you will report to the Head of ML Platform- Senior Staff Software Engineer. You will: Develop Waymo's inference platform to make it scalable, high throughput, and low latency Work closely with other teams across Waymo in hosting both internal and external ML models, including LLMs Improving the efficiency of running inference on these large models to increase throughput and save cost Deploy and integrate model inference solutions across a variety of use cases, such as distillation, eval, dataset generation, active learning, and auto-labeling You have: 5+ years of professional experience in the field of software engineering Experience in programming C++ Experience with building highly scalable distributed system We prefer: Passionate about building internal infra and tools Experience with building model hosting and inference solutions Experience with handling datasets in the order of exabytes The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $213,000-$263,000 USD
Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. We are looking for a highly technical Senior Staff/Principal Engineer to lead the porting and enablement of critical AI workloads. You will be a primary driver in migrating compute workloads to RISC-V architectures, ensuring our hardware is optimized for real-world application performance. The ideal candidate has a strong background in DevOps, workload porting, or application enablement . While this is an individual contributor role at its core, you will have the opportunity to grow and lead a small, specialized team over time as our workload migration efforts scale. This role is remote, based in the United States or Australia. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are A Technical Catalyst: You thrive on the challenge of driving AI hardware porting to RISC-V and making complex software stacks run efficiently on new hardware. Systems Expert: You possess deep knowledge of system software, compilers, or low-level OS internals. You are an expert in ARM or x86 environments and are ready to apply those skills to the RISC-V frontier. A Project Driver: You have the technical authority to lead the implementation of a compute migration to RISC-V through strategic IT and DevOps enablement. Collaborative & Cross-Functional: You enjoy acting as the "technical glue" between IT, DevOps, and AI teams , coordinating complex efforts across boundaries to ensure seamless workload transitions. Architecture Agnostic: You are a systems thinker who understands how to bridge the gap between infrastructure and core silicon engineering. What We Need Education: BS/MS/PhD in Computer Engineering, Electrical Engineering, Computer Science, or a related field. Workload Expertise: Extensive experience in workload porting, DevOps engineering, or application enablement . Systems Fluency: Strong familiarity with CPU architectures and systems design, with a proven track record of troubleshooting and optimizing performance across new architectures. Leadership Qualities: Ability to coordinate across multiple technical teams and the potential to mentor or grow a small engineering pod. Execution Focus: A mindset geared toward technical delivery and methodology development rather than broad community networking. What You Will Learn Gain deep expertise in bleeding-edge RISC-V system software across server and AI-accelerated environments. Directly influence an upcoming project , a high-visibility initiative shaping the future of our internal compute infrastructure. Work at the intersection of AI/ML workloads and hardware/software co-design. Shape the technical roadmap for how the industry adopts RISC-V for high-performance compute. Compensation for all engineers at Tenstorrent ranges from $100k - $500k including base and variable compensation targets. Experience, skills, education, background and location all impact the actual offer made. Tenstorrent offers a highly competitive compensation package and benefits, and we are an equal opportunity employer. This offer of employment is contingent upon the applicant being eligible to access U.S. export-controlled technology. Due to U.S. export laws, including those codified in the U.S. Export Administration Regulations (EAR), the Company is required to ensure compliance with these laws when transferring technology to nationals of certain countries (such as EAR Country Groups D:1, E1, and E2). These requirements apply to persons located in the U.S. and all countries outside the U.S. As the position offered will have direct and/or indirect access to information, systems, or technologies subject to these laws, the offer may be contingent upon your citizenship/permanent residency status or ability to obtain prior license approval from the U.S. Commerce Department or applicable federal agency. If employment is not possible due to U.S. export laws, any offer of employment will be rescinded.
09/23/2026
Full time
Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. We are looking for a highly technical Senior Staff/Principal Engineer to lead the porting and enablement of critical AI workloads. You will be a primary driver in migrating compute workloads to RISC-V architectures, ensuring our hardware is optimized for real-world application performance. The ideal candidate has a strong background in DevOps, workload porting, or application enablement . While this is an individual contributor role at its core, you will have the opportunity to grow and lead a small, specialized team over time as our workload migration efforts scale. This role is remote, based in the United States or Australia. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are A Technical Catalyst: You thrive on the challenge of driving AI hardware porting to RISC-V and making complex software stacks run efficiently on new hardware. Systems Expert: You possess deep knowledge of system software, compilers, or low-level OS internals. You are an expert in ARM or x86 environments and are ready to apply those skills to the RISC-V frontier. A Project Driver: You have the technical authority to lead the implementation of a compute migration to RISC-V through strategic IT and DevOps enablement. Collaborative & Cross-Functional: You enjoy acting as the "technical glue" between IT, DevOps, and AI teams , coordinating complex efforts across boundaries to ensure seamless workload transitions. Architecture Agnostic: You are a systems thinker who understands how to bridge the gap between infrastructure and core silicon engineering. What We Need Education: BS/MS/PhD in Computer Engineering, Electrical Engineering, Computer Science, or a related field. Workload Expertise: Extensive experience in workload porting, DevOps engineering, or application enablement . Systems Fluency: Strong familiarity with CPU architectures and systems design, with a proven track record of troubleshooting and optimizing performance across new architectures. Leadership Qualities: Ability to coordinate across multiple technical teams and the potential to mentor or grow a small engineering pod. Execution Focus: A mindset geared toward technical delivery and methodology development rather than broad community networking. What You Will Learn Gain deep expertise in bleeding-edge RISC-V system software across server and AI-accelerated environments. Directly influence an upcoming project , a high-visibility initiative shaping the future of our internal compute infrastructure. Work at the intersection of AI/ML workloads and hardware/software co-design. Shape the technical roadmap for how the industry adopts RISC-V for high-performance compute. Compensation for all engineers at Tenstorrent ranges from $100k - $500k including base and variable compensation targets. Experience, skills, education, background and location all impact the actual offer made. Tenstorrent offers a highly competitive compensation package and benefits, and we are an equal opportunity employer. This offer of employment is contingent upon the applicant being eligible to access U.S. export-controlled technology. Due to U.S. export laws, including those codified in the U.S. Export Administration Regulations (EAR), the Company is required to ensure compliance with these laws when transferring technology to nationals of certain countries (such as EAR Country Groups D:1, E1, and E2). These requirements apply to persons located in the U.S. and all countries outside the U.S. As the position offered will have direct and/or indirect access to information, systems, or technologies subject to these laws, the offer may be contingent upon your citizenship/permanent residency status or ability to obtain prior license approval from the U.S. Commerce Department or applicable federal agency. If employment is not possible due to U.S. export laws, any offer of employment will be rescinded.
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The World's Most Experienced Driver -to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. Onboard Software Performance team ensures that systems running on ADV (Autonomously Driven Vehicle) meet strict performance requirements such as producing necessary outputs within strict latency targets and using an appropriately allocated amount of compute resources (CPU/GPU/TPU/RAM etc) for each respective submodule. All of this needs to be done at scale with performance guarantees of many 9s of reliability while enabling high velocity of system evolution. In this hybrid role, you will report to a Senior Staff Engineer, Technical Lead Manager. You will: Develop ADV's modular architecture improvements and frameworks that maximize performance and compute utilization and ROI for driving quality Evolve our compute usage on the car and simulation to enable continued scaling where the system runs fast on the car and efficiently in our data center Collaborating with onboard teams to identify and improve compute performance bottlenecks across the stack to improve performance/driving quality Collaborating with hardware teams to codesign hardware/software and optimize the software for best performance on our hardware platform Ensuring our performance is strong at any driving complexity including as we scale to even more complex driving environments and encounter rarer events Ensuring state of the art reaction latency for collision avoidance via novel system/architecture designs and extremely fast nominal performance Developing necessary high scale performance evaluation, debugging and software change management processes Optimizing system resource usage to simulation at scale in Cloud datacenters: minimizing CPU utilization and latency, minimizing RAM consumption, intelligently determining which computations should happen on CPU, GPU, and TPU. You have: BS/MS in Comp Sci, EE, Robotics, Physics, Math, or related field (or equivalent experience) 6 years of software engineering experience on large scale/high complexity system (supported by hundreds of engineers) 2 years of software management experience with at least 4 years in infrastructure/systems/performance domain optimizing end to end system for high performance metrics 4 years of experience acting as technical lead in performance/software infrastructure domain 4 years of experience in C++ Define roadmap/portfolio of projects optimizing for end results overall across all aspects of the problem space Setup collaboration structures across team boundaries We prefer: Experience in robotics Experience in low level optimization techniques, frameworks (SIMD/CUDA) and ML performance/frameworks Experience in large scale evaluation techniques/data science and building performance metrics/tooling Experience in large scale software re-architecture projects The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $238,000-$302,000 USD
09/23/2026
Full time
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The World's Most Experienced Driver -to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. Onboard Software Performance team ensures that systems running on ADV (Autonomously Driven Vehicle) meet strict performance requirements such as producing necessary outputs within strict latency targets and using an appropriately allocated amount of compute resources (CPU/GPU/TPU/RAM etc) for each respective submodule. All of this needs to be done at scale with performance guarantees of many 9s of reliability while enabling high velocity of system evolution. In this hybrid role, you will report to a Senior Staff Engineer, Technical Lead Manager. You will: Develop ADV's modular architecture improvements and frameworks that maximize performance and compute utilization and ROI for driving quality Evolve our compute usage on the car and simulation to enable continued scaling where the system runs fast on the car and efficiently in our data center Collaborating with onboard teams to identify and improve compute performance bottlenecks across the stack to improve performance/driving quality Collaborating with hardware teams to codesign hardware/software and optimize the software for best performance on our hardware platform Ensuring our performance is strong at any driving complexity including as we scale to even more complex driving environments and encounter rarer events Ensuring state of the art reaction latency for collision avoidance via novel system/architecture designs and extremely fast nominal performance Developing necessary high scale performance evaluation, debugging and software change management processes Optimizing system resource usage to simulation at scale in Cloud datacenters: minimizing CPU utilization and latency, minimizing RAM consumption, intelligently determining which computations should happen on CPU, GPU, and TPU. You have: BS/MS in Comp Sci, EE, Robotics, Physics, Math, or related field (or equivalent experience) 6 years of software engineering experience on large scale/high complexity system (supported by hundreds of engineers) 2 years of software management experience with at least 4 years in infrastructure/systems/performance domain optimizing end to end system for high performance metrics 4 years of experience acting as technical lead in performance/software infrastructure domain 4 years of experience in C++ Define roadmap/portfolio of projects optimizing for end results overall across all aspects of the problem space Setup collaboration structures across team boundaries We prefer: Experience in robotics Experience in low level optimization techniques, frameworks (SIMD/CUDA) and ML performance/frameworks Experience in large scale evaluation techniques/data science and building performance metrics/tooling Experience in large scale software re-architecture projects The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $238,000-$302,000 USD
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The World's Most Experienced Driver -to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. The DUE Machine Learning team will build and operate scalable machine learning and data systems, simulation workflow and insight tools, improve and speed up the evaluation and onboard developer journeys. It will combine expert human judgements and advanced machine learning models to deliver training and evaluation data for hundreds of metrics and components that make up the Waymo Driver. We are looking for researchers and software engineers who are passionate about developing machine learning techniques. These techniques are for the Evaluation systems on our autonomous service. They will serve as a constant driver to improve the performance of our technology stack. You will: Grow the end-to-end strategy for our next generation of machine learning-based evaluation metrics, promoting scientific and statistical rigor across our embodied AI applications Architect and build scalable systems for training and fine-tuning large-scale generative models to produce realistic and evaluate interesting driving behaviors Lead the design, implementation, and iteration of novel RL algorithms, reward functions, and training paradigms tailored for generating high-fidelity and insightful driving behaviors Lead the development of cutting-edge Deep Learning models and Generative AI (LLM/VLM) solutions. These solutions will enhance human-led triaging, introduce automation for high-volume workflows, and perform nuanced analysis of self-driving behavior to detect critical anomalies Proactively monitor and assimilate best practices from within Alphabet and the broader industry to develop a novel Reinforcement Learning from Human Preference (RLHF) based data collection and evaluation system Provide technical mentorship, guidance, and thought leadership to other engineers within the team and across collaborating groups Guide and align multiple teams-including Driver Understanding, Simulation, System Engineering, Research, and Onboard Software-on a cohesive evaluation strategy, ensuring cross-functional alignment on goals and priorities You have: PhD degree in Computer Science, Machine Learning, Artificial Intelligence, or a related technical field, or equivalent practical experience 10+ years of hands-on experience in developing and applying Machine Learning models, with a significant focus on Reinforcement Learning 2+ years of people management experience Demonstrated expertise in deep learning, sequence modeling, and generative models Strong publication record or history of impactful project delivery in RL or related areas Proficiency in Python and standard ML frameworks (e.g., JAX, TensorFlow) Experience with large-scale distributed training and data processing Proven ability to lead complex and ambiguous technical projects from conception to completion We prefer: 12+ years of relevant experience in ML/RL research and application Experience in the autonomous vehicles domain, robotics, or complex simulation environments Deep understanding of state-of-the-art RL techniques, including those used for fine-tuning large models (e.g., from human feedback/preferences) Familiarity with large-scale simulation platforms and their integration with ML training workflows Experience designing and using metrics for evaluating complex AI systems Track record of technical leadership, influencing senior stakeholders, and driving innovation across team boundaries Excellent communication skills, with the ability to articulate complex technical concepts clearly The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $281,000-$356,000 USD
09/23/2026
Full time
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The World's Most Experienced Driver -to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. The DUE Machine Learning team will build and operate scalable machine learning and data systems, simulation workflow and insight tools, improve and speed up the evaluation and onboard developer journeys. It will combine expert human judgements and advanced machine learning models to deliver training and evaluation data for hundreds of metrics and components that make up the Waymo Driver. We are looking for researchers and software engineers who are passionate about developing machine learning techniques. These techniques are for the Evaluation systems on our autonomous service. They will serve as a constant driver to improve the performance of our technology stack. You will: Grow the end-to-end strategy for our next generation of machine learning-based evaluation metrics, promoting scientific and statistical rigor across our embodied AI applications Architect and build scalable systems for training and fine-tuning large-scale generative models to produce realistic and evaluate interesting driving behaviors Lead the design, implementation, and iteration of novel RL algorithms, reward functions, and training paradigms tailored for generating high-fidelity and insightful driving behaviors Lead the development of cutting-edge Deep Learning models and Generative AI (LLM/VLM) solutions. These solutions will enhance human-led triaging, introduce automation for high-volume workflows, and perform nuanced analysis of self-driving behavior to detect critical anomalies Proactively monitor and assimilate best practices from within Alphabet and the broader industry to develop a novel Reinforcement Learning from Human Preference (RLHF) based data collection and evaluation system Provide technical mentorship, guidance, and thought leadership to other engineers within the team and across collaborating groups Guide and align multiple teams-including Driver Understanding, Simulation, System Engineering, Research, and Onboard Software-on a cohesive evaluation strategy, ensuring cross-functional alignment on goals and priorities You have: PhD degree in Computer Science, Machine Learning, Artificial Intelligence, or a related technical field, or equivalent practical experience 10+ years of hands-on experience in developing and applying Machine Learning models, with a significant focus on Reinforcement Learning 2+ years of people management experience Demonstrated expertise in deep learning, sequence modeling, and generative models Strong publication record or history of impactful project delivery in RL or related areas Proficiency in Python and standard ML frameworks (e.g., JAX, TensorFlow) Experience with large-scale distributed training and data processing Proven ability to lead complex and ambiguous technical projects from conception to completion We prefer: 12+ years of relevant experience in ML/RL research and application Experience in the autonomous vehicles domain, robotics, or complex simulation environments Deep understanding of state-of-the-art RL techniques, including those used for fine-tuning large models (e.g., from human feedback/preferences) Familiarity with large-scale simulation platforms and their integration with ML training workflows Experience designing and using metrics for evaluating complex AI systems Track record of technical leadership, influencing senior stakeholders, and driving innovation across team boundaries Excellent communication skills, with the ability to articulate complex technical concepts clearly The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $281,000-$356,000 USD
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The World's Most Experienced Driver -to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. The Driver Understanding and Evaluation (DUE) team at Waymo is developing rich metrics for understanding the behavior of the Waymo Driver in the real world, and technologies such as context and scene analysis to understand driving, understanding and augmenting real world driving data to generate rare driving events, build large scale data infrastructure, improve components such as agents and a realistic simulator. These technologies come together to drive the overall technical strategy and methodology used to evaluate the behavior of the Waymo Driver. The DUE Machine Learning team will build and operate scalable machine learning and data systems, simulation workflow and insight tools, improve and speed up the evaluation and onboard developer journeys. It will combine expert human judgements and advanced machine learning models to deliver training and evaluation data for hundreds of metrics and components that make up the Waymo driver. We are looking for researchers and software engineers who are passionate about developing machine learning techniques for the Evaluation systems on our autonomous vehicles, and have an incessant drive to improve the performance of our technology stack. You will: Lead the development of cutting edge Deep Learning and machine learning models to enhance human-led triaging and introduce automation for high-volume workflows Design and build Gen AI LLM/VLM solutions for self driving car behavior analysis and anomaly detection Proactively monitor and assimilate best practices from within Alphabet and the broader industry to develop a Reinforcement Learning from human preference-based data collection and evaluation system. Enhance User Feedback Analysis, collaborate seamlessly with product and business teams to design and implement tools for multi-label classifications, sentiment assessment, comment summarization, root cause analysis and trend analysis of rider feedback Oversee the production and optimization of machine learning models aiming to assess Waymo's expansive fleet of vehicles that cumulatively travel millions of miles. Drive technical direction, and provide technical inputs and guidance to the team. Work closely with PMs and TPMs to help define product requirements and align the technical agenda with the company's business objectives. Collaborate closely with multiple teams (e.g., Prediction, Planning, Research), other technical leads, and senior leaderships across Waymo to deliver on key strategic efforts. You have: B.S. in Computer Science, Robotics, Machine Learning, similar technical field of study, or equivalent practical experience 7+ years of experience with hands-on experience in machine learning projects Strong coding experience in C++ and/or Python. Experience in at least one of: Foundational Models, VLM, Deep Learning Experience with ML frameworks such as TensorFlow, PyTorch, Hugging Face's transformers, along with expertise in deep learning models and ML deployment at scale We prefer: M.S. or Ph.D. degree Computer Science or related quantitative field with a specialization of machine learning. 10+ years of experience with hands-on experience in machine learning projects Deep learning experience with Transformers Gen AI LLM/VLM experience Experience with building tools for applied machine learning, including MLOps, evaluation/validation techniques, and model performance optimization. Large-scale data processing and analytical skills. The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $238,000-$302,000 USD
09/23/2026
Full time
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The World's Most Experienced Driver -to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. The Driver Understanding and Evaluation (DUE) team at Waymo is developing rich metrics for understanding the behavior of the Waymo Driver in the real world, and technologies such as context and scene analysis to understand driving, understanding and augmenting real world driving data to generate rare driving events, build large scale data infrastructure, improve components such as agents and a realistic simulator. These technologies come together to drive the overall technical strategy and methodology used to evaluate the behavior of the Waymo Driver. The DUE Machine Learning team will build and operate scalable machine learning and data systems, simulation workflow and insight tools, improve and speed up the evaluation and onboard developer journeys. It will combine expert human judgements and advanced machine learning models to deliver training and evaluation data for hundreds of metrics and components that make up the Waymo driver. We are looking for researchers and software engineers who are passionate about developing machine learning techniques for the Evaluation systems on our autonomous vehicles, and have an incessant drive to improve the performance of our technology stack. You will: Lead the development of cutting edge Deep Learning and machine learning models to enhance human-led triaging and introduce automation for high-volume workflows Design and build Gen AI LLM/VLM solutions for self driving car behavior analysis and anomaly detection Proactively monitor and assimilate best practices from within Alphabet and the broader industry to develop a Reinforcement Learning from human preference-based data collection and evaluation system. Enhance User Feedback Analysis, collaborate seamlessly with product and business teams to design and implement tools for multi-label classifications, sentiment assessment, comment summarization, root cause analysis and trend analysis of rider feedback Oversee the production and optimization of machine learning models aiming to assess Waymo's expansive fleet of vehicles that cumulatively travel millions of miles. Drive technical direction, and provide technical inputs and guidance to the team. Work closely with PMs and TPMs to help define product requirements and align the technical agenda with the company's business objectives. Collaborate closely with multiple teams (e.g., Prediction, Planning, Research), other technical leads, and senior leaderships across Waymo to deliver on key strategic efforts. You have: B.S. in Computer Science, Robotics, Machine Learning, similar technical field of study, or equivalent practical experience 7+ years of experience with hands-on experience in machine learning projects Strong coding experience in C++ and/or Python. Experience in at least one of: Foundational Models, VLM, Deep Learning Experience with ML frameworks such as TensorFlow, PyTorch, Hugging Face's transformers, along with expertise in deep learning models and ML deployment at scale We prefer: M.S. or Ph.D. degree Computer Science or related quantitative field with a specialization of machine learning. 10+ years of experience with hands-on experience in machine learning projects Deep learning experience with Transformers Gen AI LLM/VLM experience Experience with building tools for applied machine learning, including MLOps, evaluation/validation techniques, and model performance optimization. Large-scale data processing and analytical skills. The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $238,000-$302,000 USD
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The World's Most Experienced Driver -to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. The Driver Understanding and Evaluation team at Waymo develops a rich understanding of Waymo Driver's behavior. With over 1 million driverless miles per week, it is critical that Waymo can understand and assess the behavior of all its vehicles - both in the field and in simulation - with automated algorithms. The learned metrics team is a strategic bet to use machine learning to ensure we can scale to meet Waymo's goals. We collaborate across teams to bring ML to production systems and build what is Waymo's reward function. We build and operate large-scale machine learning and data systems, simulation workflows, and insight tools. We combine expert human judgements and advanced machine learning models to deliver training and evaluation data for the Waymo driver. We are looking for researchers and software engineers who are passionate about developing production grade machine learning systems for our autonomous vehicles and have an incessant drive to improve the performance of our technology stack. This role follows a hybrid work schedule and reports to an Engineering Manager. You will: Lead a top-tier applied ML team focused on building ML models for AV behavior understanding and evaluation, using deep learning and Gen AI. Lead the development of cutting edge Deep Learning and machine learning models to enhance human-led triaging and introduce automation for high-volume workflows Design and build Gen AI LLM/VLM solutions for self driving car behavior analysis and anomaly detection Enhance User Feedback Analysis, collaborate seamlessly with product and business teams to design and implement tools for multi-label classifications, sentiment assessment, comment summarization, root cause analysis and trend analysis of rider feedback Oversee the production and optimization of machine learning models aiming to assess Waymo's expansive fleet of vehicles that cumulatively travel millions of miles. Drive technical direction, and provide technical inputs and guidance to the team. Work closely with PMs and TPMs to help define product requirements and align the technical agenda with the company's business objectives. Collaborate closely with multiple teams (e.g., Prediction, Planning, Research), other technical leads, and senior leaderships across Waymo to deliver on key strategic efforts. You have: B.S. in Computer Science, Robotics, Machine Learning, similar technical field of study, or equivalent practical experience 5+ years of experience leading engineering teams of 5-15 people 7+ years of experience with hands-on experience in machine learning projects 7+ years of hands-on experience building and deploying machine learning products in production environments Experience in at least one of: Foundational Models, VLM, Deep Learning Strong coding experience in C++ and/or Python. Experience with ML frameworks such as TensorFlow, PyTorch, Hugging Face's transformers, along with expertise in deep learning models and ML deployment at scale We prefer: M.S. or Ph.D. degree Computer Science or related quantitative field with a specialization of machine learning. Deep learning experience with Transformers Gen AI LLM/VLM experience Experience with building tools for applied machine learning, including MLOps, evaluation/validation techniques, and model performance optimization. Large-scale data processing and analytical skills. The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $238,000-$302,000 USD
09/23/2026
Full time
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The World's Most Experienced Driver -to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. The Driver Understanding and Evaluation team at Waymo develops a rich understanding of Waymo Driver's behavior. With over 1 million driverless miles per week, it is critical that Waymo can understand and assess the behavior of all its vehicles - both in the field and in simulation - with automated algorithms. The learned metrics team is a strategic bet to use machine learning to ensure we can scale to meet Waymo's goals. We collaborate across teams to bring ML to production systems and build what is Waymo's reward function. We build and operate large-scale machine learning and data systems, simulation workflows, and insight tools. We combine expert human judgements and advanced machine learning models to deliver training and evaluation data for the Waymo driver. We are looking for researchers and software engineers who are passionate about developing production grade machine learning systems for our autonomous vehicles and have an incessant drive to improve the performance of our technology stack. This role follows a hybrid work schedule and reports to an Engineering Manager. You will: Lead a top-tier applied ML team focused on building ML models for AV behavior understanding and evaluation, using deep learning and Gen AI. Lead the development of cutting edge Deep Learning and machine learning models to enhance human-led triaging and introduce automation for high-volume workflows Design and build Gen AI LLM/VLM solutions for self driving car behavior analysis and anomaly detection Enhance User Feedback Analysis, collaborate seamlessly with product and business teams to design and implement tools for multi-label classifications, sentiment assessment, comment summarization, root cause analysis and trend analysis of rider feedback Oversee the production and optimization of machine learning models aiming to assess Waymo's expansive fleet of vehicles that cumulatively travel millions of miles. Drive technical direction, and provide technical inputs and guidance to the team. Work closely with PMs and TPMs to help define product requirements and align the technical agenda with the company's business objectives. Collaborate closely with multiple teams (e.g., Prediction, Planning, Research), other technical leads, and senior leaderships across Waymo to deliver on key strategic efforts. You have: B.S. in Computer Science, Robotics, Machine Learning, similar technical field of study, or equivalent practical experience 5+ years of experience leading engineering teams of 5-15 people 7+ years of experience with hands-on experience in machine learning projects 7+ years of hands-on experience building and deploying machine learning products in production environments Experience in at least one of: Foundational Models, VLM, Deep Learning Strong coding experience in C++ and/or Python. Experience with ML frameworks such as TensorFlow, PyTorch, Hugging Face's transformers, along with expertise in deep learning models and ML deployment at scale We prefer: M.S. or Ph.D. degree Computer Science or related quantitative field with a specialization of machine learning. Deep learning experience with Transformers Gen AI LLM/VLM experience Experience with building tools for applied machine learning, including MLOps, evaluation/validation techniques, and model performance optimization. Large-scale data processing and analytical skills. The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $238,000-$302,000 USD
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The World's Most Experienced Driver -to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. The Driver Understanding and Evaluation team at Waymo develops a rich understanding of Waymo Driver's behavior. With over 1 million driverless miles per week, it is critical that Waymo can understand and assess the behavior of all its vehicles - both in the field and in simulation - with automated algorithms. The learned metrics team is a strategic bet to use machine learning to ensure we can scale to meet Waymo's goals. We collaborate across teams to bring ML to production systems and build what is Waymo's reward function. We build and operate large-scale machine learning and data systems, simulation workflows, and insight tools. We combine expert human judgements and advanced machine learning models to deliver training and evaluation data for the Waymo driver. We are looking for researchers and software engineers who are passionate about developing production grade machine learning systems for our autonomous vehicles and have an incessant drive to improve the performance of our technology stack. This role follows a hybrid work schedule and reports to an Engineering Manager. You will: Lead a top-tier applied ML team focused on building ML models for AV behavior understanding and evaluation, using deep learning and Gen AI. Lead the development of cutting edge Deep Learning and machine learning models to enhance human-led triaging and introduce automation for high-volume workflows Design and build Gen AI LLM/VLM solutions for self driving car behavior analysis and anomaly detection Enhance User Feedback Analysis, collaborate seamlessly with product and business teams to design and implement tools for multi-label classifications, sentiment assessment, comment summarization, root cause analysis and trend analysis of rider feedback Oversee the production and optimization of machine learning models aiming to assess Waymo's expansive fleet of vehicles that cumulatively travel millions of miles. Drive technical direction, and provide technical inputs and guidance to the team. Work closely with PMs and TPMs to help define product requirements and align the technical agenda with the company's business objectives. Collaborate closely with multiple teams (e.g., Prediction, Planning, Research), other technical leads, and senior leaderships across Waymo to deliver on key strategic efforts. You have: B.S. in Computer Science, Robotics, Machine Learning, similar technical field of study, or equivalent practical experience 5+ years of experience leading engineering teams of 5-15 people 7+ years of experience with hands-on experience in machine learning projects 7+ years of hands-on experience building and deploying machine learning products in production environments Experience in at least one of: Foundational Models, VLM, Deep Learning Strong coding experience in C++ and/or Python. Experience with ML frameworks such as TensorFlow, PyTorch, Hugging Face's transformers, along with expertise in deep learning models and ML deployment at scale We prefer: M.S. or Ph.D. degree Computer Science or related quantitative field with a specialization of machine learning. Deep learning experience with Transformers Gen AI LLM/VLM experience Experience with building tools for applied machine learning, including MLOps, evaluation/validation techniques, and model performance optimization. Large-scale data processing and analytical skills. The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $238,000-$302,000 USD
09/23/2026
Full time
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The World's Most Experienced Driver -to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. The Driver Understanding and Evaluation team at Waymo develops a rich understanding of Waymo Driver's behavior. With over 1 million driverless miles per week, it is critical that Waymo can understand and assess the behavior of all its vehicles - both in the field and in simulation - with automated algorithms. The learned metrics team is a strategic bet to use machine learning to ensure we can scale to meet Waymo's goals. We collaborate across teams to bring ML to production systems and build what is Waymo's reward function. We build and operate large-scale machine learning and data systems, simulation workflows, and insight tools. We combine expert human judgements and advanced machine learning models to deliver training and evaluation data for the Waymo driver. We are looking for researchers and software engineers who are passionate about developing production grade machine learning systems for our autonomous vehicles and have an incessant drive to improve the performance of our technology stack. This role follows a hybrid work schedule and reports to an Engineering Manager. You will: Lead a top-tier applied ML team focused on building ML models for AV behavior understanding and evaluation, using deep learning and Gen AI. Lead the development of cutting edge Deep Learning and machine learning models to enhance human-led triaging and introduce automation for high-volume workflows Design and build Gen AI LLM/VLM solutions for self driving car behavior analysis and anomaly detection Enhance User Feedback Analysis, collaborate seamlessly with product and business teams to design and implement tools for multi-label classifications, sentiment assessment, comment summarization, root cause analysis and trend analysis of rider feedback Oversee the production and optimization of machine learning models aiming to assess Waymo's expansive fleet of vehicles that cumulatively travel millions of miles. Drive technical direction, and provide technical inputs and guidance to the team. Work closely with PMs and TPMs to help define product requirements and align the technical agenda with the company's business objectives. Collaborate closely with multiple teams (e.g., Prediction, Planning, Research), other technical leads, and senior leaderships across Waymo to deliver on key strategic efforts. You have: B.S. in Computer Science, Robotics, Machine Learning, similar technical field of study, or equivalent practical experience 5+ years of experience leading engineering teams of 5-15 people 7+ years of experience with hands-on experience in machine learning projects 7+ years of hands-on experience building and deploying machine learning products in production environments Experience in at least one of: Foundational Models, VLM, Deep Learning Strong coding experience in C++ and/or Python. Experience with ML frameworks such as TensorFlow, PyTorch, Hugging Face's transformers, along with expertise in deep learning models and ML deployment at scale We prefer: M.S. or Ph.D. degree Computer Science or related quantitative field with a specialization of machine learning. Deep learning experience with Transformers Gen AI LLM/VLM experience Experience with building tools for applied machine learning, including MLOps, evaluation/validation techniques, and model performance optimization. Large-scale data processing and analytical skills. The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $238,000-$302,000 USD
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The World's Most Experienced Driver -to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. The Driver Understanding and Evaluation team at Waymo develops a rich understanding of Waymo Driver's behavior. With over 1 million driverless miles per week, it is critical that Waymo can understand and assess the behavior of all its vehicles - both in the field and in simulation - with automated algorithms. The learned metrics team is a strategic bet to use machine learning to ensure we can scale to meet Waymo's goals. We collaborate across teams to bring ML to production systems and build what is Waymo's reward function. We build and operate large-scale machine learning and data systems, simulation workflows, and insight tools. We combine expert human judgements and advanced machine learning models to deliver training and evaluation data for the Waymo driver. We are looking for researchers and software engineers who are passionate about developing production grade machine learning systems for our autonomous vehicles and have an incessant drive to improve the performance of our technology stack. This role follows a hybrid work schedule and reports to an Engineering Manager. You will: Lead a top-tier applied ML team focused on building ML models for AV behavior understanding and evaluation, using deep learning and Gen AI. Lead the development of cutting edge Deep Learning and machine learning models to enhance human-led triaging and introduce automation for high-volume workflows Design and build Gen AI LLM/VLM solutions for self driving car behavior analysis and anomaly detection Enhance User Feedback Analysis, collaborate seamlessly with product and business teams to design and implement tools for multi-label classifications, sentiment assessment, comment summarization, root cause analysis and trend analysis of rider feedback Oversee the production and optimization of machine learning models aiming to assess Waymo's expansive fleet of vehicles that cumulatively travel millions of miles. Drive technical direction, and provide technical inputs and guidance to the team. Work closely with PMs and TPMs to help define product requirements and align the technical agenda with the company's business objectives. Collaborate closely with multiple teams (e.g., Prediction, Planning, Research), other technical leads, and senior leaderships across Waymo to deliver on key strategic efforts. You have: B.S. in Computer Science, Robotics, Machine Learning, similar technical field of study, or equivalent practical experience 5+ years of experience leading engineering teams of 5-15 people 7+ years of experience with hands-on experience in machine learning projects 7+ years of hands-on experience building and deploying machine learning products in production environments Experience in at least one of: Foundational Models, VLM, Deep Learning Strong coding experience in C++ and/or Python. Experience with ML frameworks such as TensorFlow, PyTorch, Hugging Face's transformers, along with expertise in deep learning models and ML deployment at scale We prefer: M.S. or Ph.D. degree Computer Science or related quantitative field with a specialization of machine learning. Deep learning experience with Transformers Gen AI LLM/VLM experience Experience with building tools for applied machine learning, including MLOps, evaluation/validation techniques, and model performance optimization. Large-scale data processing and analytical skills. The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $238,000-$302,000 USD
09/23/2026
Full time
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The World's Most Experienced Driver -to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. The Driver Understanding and Evaluation team at Waymo develops a rich understanding of Waymo Driver's behavior. With over 1 million driverless miles per week, it is critical that Waymo can understand and assess the behavior of all its vehicles - both in the field and in simulation - with automated algorithms. The learned metrics team is a strategic bet to use machine learning to ensure we can scale to meet Waymo's goals. We collaborate across teams to bring ML to production systems and build what is Waymo's reward function. We build and operate large-scale machine learning and data systems, simulation workflows, and insight tools. We combine expert human judgements and advanced machine learning models to deliver training and evaluation data for the Waymo driver. We are looking for researchers and software engineers who are passionate about developing production grade machine learning systems for our autonomous vehicles and have an incessant drive to improve the performance of our technology stack. This role follows a hybrid work schedule and reports to an Engineering Manager. You will: Lead a top-tier applied ML team focused on building ML models for AV behavior understanding and evaluation, using deep learning and Gen AI. Lead the development of cutting edge Deep Learning and machine learning models to enhance human-led triaging and introduce automation for high-volume workflows Design and build Gen AI LLM/VLM solutions for self driving car behavior analysis and anomaly detection Enhance User Feedback Analysis, collaborate seamlessly with product and business teams to design and implement tools for multi-label classifications, sentiment assessment, comment summarization, root cause analysis and trend analysis of rider feedback Oversee the production and optimization of machine learning models aiming to assess Waymo's expansive fleet of vehicles that cumulatively travel millions of miles. Drive technical direction, and provide technical inputs and guidance to the team. Work closely with PMs and TPMs to help define product requirements and align the technical agenda with the company's business objectives. Collaborate closely with multiple teams (e.g., Prediction, Planning, Research), other technical leads, and senior leaderships across Waymo to deliver on key strategic efforts. You have: B.S. in Computer Science, Robotics, Machine Learning, similar technical field of study, or equivalent practical experience 5+ years of experience leading engineering teams of 5-15 people 7+ years of experience with hands-on experience in machine learning projects 7+ years of hands-on experience building and deploying machine learning products in production environments Experience in at least one of: Foundational Models, VLM, Deep Learning Strong coding experience in C++ and/or Python. Experience with ML frameworks such as TensorFlow, PyTorch, Hugging Face's transformers, along with expertise in deep learning models and ML deployment at scale We prefer: M.S. or Ph.D. degree Computer Science or related quantitative field with a specialization of machine learning. Deep learning experience with Transformers Gen AI LLM/VLM experience Experience with building tools for applied machine learning, including MLOps, evaluation/validation techniques, and model performance optimization. Large-scale data processing and analytical skills. The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $238,000-$302,000 USD
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The World's Most Experienced Driver -to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. The Perception Team at Waymo builds the system that "sees" the world around the self-driving car. We conduct novel research to address real-world perception problems and collaborate with research teams at Alphabet. Here at Waymo, we have access to millions of miles of driving data from a diverse set of sensors, enabling researchers like you to develop complex models and techniques at scale. Improvements deployed to our system can immediately advance our large fleet of autonomous vehicles. Within Perception, the Sensor Health team's job is to make sure that sensors "just work" for the entire self-driving car software stack. We make sure that all sensors are properly calibrated and consistently monitored at all times. We process data from next-generation sensors on next-generation vehicle platforms and work closely with both hardware and software teams to provide the best possible sensor data from our sensors to our upstream customers. To this end, we develop sensor data alignment and calibration algorithms, a growing sensor health backend, and deploy our systems both into the Waymo Driver and our log processing backend. In this hybrid remote/in-office role, you will report to a Senior Staff TLM. You will: Lead and build a team of ML engineers in charge of reliable sensing anomaly detection and calibration Build a data flywheel to automatically generate suitable training data for rare instance sensor degradation events using VLMs Own the entire sensor validation stack end to end Drive and accelerate collaborations between perception, system engineering, evaluation, and Alphabet teams You have: MS in Computer Science, Robotics, Math, Physics or equivalent industry experience 6+ years of experience in designing, training, and deploying ML-driven real-time robotics systems 4+ years of experience leading technical teams and setting technical directions 2+ years of people management experience We prefer: PhD in Computer Science, Robotics, Math, Physics, or a related technical field Experience in robotics, autonomous systems, or related automotive industries. Experience with various sensor modalities (e.g., LiDAR, radar, cameras) and their unique challenges. Familiarity with early fusion multi modal sensor models and their development challenges Experience with rare instance or zero-shot detection problems The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $238,000-$302,000 USD
09/23/2026
Full time
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The World's Most Experienced Driver -to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. The Perception Team at Waymo builds the system that "sees" the world around the self-driving car. We conduct novel research to address real-world perception problems and collaborate with research teams at Alphabet. Here at Waymo, we have access to millions of miles of driving data from a diverse set of sensors, enabling researchers like you to develop complex models and techniques at scale. Improvements deployed to our system can immediately advance our large fleet of autonomous vehicles. Within Perception, the Sensor Health team's job is to make sure that sensors "just work" for the entire self-driving car software stack. We make sure that all sensors are properly calibrated and consistently monitored at all times. We process data from next-generation sensors on next-generation vehicle platforms and work closely with both hardware and software teams to provide the best possible sensor data from our sensors to our upstream customers. To this end, we develop sensor data alignment and calibration algorithms, a growing sensor health backend, and deploy our systems both into the Waymo Driver and our log processing backend. In this hybrid remote/in-office role, you will report to a Senior Staff TLM. You will: Lead and build a team of ML engineers in charge of reliable sensing anomaly detection and calibration Build a data flywheel to automatically generate suitable training data for rare instance sensor degradation events using VLMs Own the entire sensor validation stack end to end Drive and accelerate collaborations between perception, system engineering, evaluation, and Alphabet teams You have: MS in Computer Science, Robotics, Math, Physics or equivalent industry experience 6+ years of experience in designing, training, and deploying ML-driven real-time robotics systems 4+ years of experience leading technical teams and setting technical directions 2+ years of people management experience We prefer: PhD in Computer Science, Robotics, Math, Physics, or a related technical field Experience in robotics, autonomous systems, or related automotive industries. Experience with various sensor modalities (e.g., LiDAR, radar, cameras) and their unique challenges. Familiarity with early fusion multi modal sensor models and their development challenges Experience with rare instance or zero-shot detection problems The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $238,000-$302,000 USD
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The World's Most Experienced Driver -to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. The Perception Team at Waymo builds the system that "sees" the world around the self-driving car. We conduct novel research to address real-world perception problems and collaborate with research teams at Alphabet. Here at Waymo, we have access to millions of miles of driving data from a diverse set of sensors, enabling researchers like you to develop complex models and techniques at scale. Improvements deployed to our system can immediately advance our large fleet of autonomous vehicles. Within Perception, the Sensor Health team's job is to make sure that sensors "just work" for the entire self-driving car software stack. We make sure that all sensors are properly calibrated and consistently monitored at all times. We process data from next-generation sensors on next-generation vehicle platforms and work closely with both hardware and software teams to provide the best possible sensor data from our sensors to our upstream customers. To this end, we develop sensor data alignment and calibration algorithms, a growing sensor health backend, and deploy our systems both into the Waymo Driver and our log processing backend. In this hybrid remote/in-office role, you will report to a Senior Staff TLM. You will: Lead and build a team of ML engineers in charge of reliable sensing anomaly detection and calibration Build a data flywheel to automatically generate suitable training data for rare instance sensor degradation events using VLMs Own the entire sensor validation stack end to end Drive and accelerate collaborations between perception, system engineering, evaluation, and Alphabet teams You have: MS in Computer Science, Robotics, Math, Physics or equivalent industry experience 6+ years of experience in designing, training, and deploying ML-driven real-time robotics systems 4+ years of experience leading technical teams and setting technical directions 2+ years of people management experience We prefer: PhD in Computer Science, Robotics, Math, Physics, or a related technical field Experience in robotics, autonomous systems, or related automotive industries. Experience with various sensor modalities (e.g., LiDAR, radar, cameras) and their unique challenges. Familiarity with early fusion multi modal sensor models and their development challenges Experience with rare instance or zero-shot detection problems The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $238,000-$302,000 USD
09/23/2026
Full time
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The World's Most Experienced Driver -to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. The Perception Team at Waymo builds the system that "sees" the world around the self-driving car. We conduct novel research to address real-world perception problems and collaborate with research teams at Alphabet. Here at Waymo, we have access to millions of miles of driving data from a diverse set of sensors, enabling researchers like you to develop complex models and techniques at scale. Improvements deployed to our system can immediately advance our large fleet of autonomous vehicles. Within Perception, the Sensor Health team's job is to make sure that sensors "just work" for the entire self-driving car software stack. We make sure that all sensors are properly calibrated and consistently monitored at all times. We process data from next-generation sensors on next-generation vehicle platforms and work closely with both hardware and software teams to provide the best possible sensor data from our sensors to our upstream customers. To this end, we develop sensor data alignment and calibration algorithms, a growing sensor health backend, and deploy our systems both into the Waymo Driver and our log processing backend. In this hybrid remote/in-office role, you will report to a Senior Staff TLM. You will: Lead and build a team of ML engineers in charge of reliable sensing anomaly detection and calibration Build a data flywheel to automatically generate suitable training data for rare instance sensor degradation events using VLMs Own the entire sensor validation stack end to end Drive and accelerate collaborations between perception, system engineering, evaluation, and Alphabet teams You have: MS in Computer Science, Robotics, Math, Physics or equivalent industry experience 6+ years of experience in designing, training, and deploying ML-driven real-time robotics systems 4+ years of experience leading technical teams and setting technical directions 2+ years of people management experience We prefer: PhD in Computer Science, Robotics, Math, Physics, or a related technical field Experience in robotics, autonomous systems, or related automotive industries. Experience with various sensor modalities (e.g., LiDAR, radar, cameras) and their unique challenges. Familiarity with early fusion multi modal sensor models and their development challenges Experience with rare instance or zero-shot detection problems The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $238,000-$302,000 USD
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The World's Most Experienced Driver -to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. Software Engineering builds the brains of Waymo's fully autonomous driving technology. Our software allows the Waymo Driver to perceive the world around it, make the right decision for every situation, and deliver people safely to their destinations. We think deeply and solve complex technical challenges in areas like robotics, perception, decision-making and deep learning, while collaborating with hardware and systems engineers. If you're a software engineer or researcher who's curious and passionate about Level 4 autonomous driving, we'd like to meet you. The Sensor Foundations Team's purpose is to provide cleaned-up sensor data through highly optimized APIs to Perception models, to abstract sensor hardware differences where possible, and to provide low-level Perception signals either through algorithms or machine learning. Projects on our team typically require a diverse skill set, including robotics, system integration, code optimization, and machine learning. We have a good understanding of the hardware (both sensors and compute) and the overall Perception system. The Optimization sub-team uses our know-how of CPUs, GPUs, and clever algorithms to process Waymo's sensor data super-fast and feed it to the Perception ML models. We specialize in low-level understanding of compute hardware, and we apply that knowledge wherever we can, throughout the whole stack. We are looking for a Tech-Lead Manager with a CPU, GPU, or system-level optimization background to lead this small team of Software Engineers. Depending on your prior experience, you may also be responsible for system-level optimization and be a steward of our compute resources. This role follows a hybrid work schedule and reports to the TLM of the Sensor Foundations team. You will: Lead a small team of optimization experts Identify system-level optimization opportunities Optimize existing CPU code Write and review CUDA code Collaborate with ML practitioners to understand their input-processing needs. Be a steward of our compute resources You have: B.Sc in Computer Science, Mathematics or a related field 8+ years of industry experience Strong C++ programming skills Experience with optimizing CPU or GPU code (ideally both) Prior people management experience We prefer: M.Sc or PhD in Computer Science, Mathematics or a related field Experience with system-level optimization Experience with compiler technology. The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $298,000-$368,000 USD
09/23/2026
Full time
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The World's Most Experienced Driver -to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. Software Engineering builds the brains of Waymo's fully autonomous driving technology. Our software allows the Waymo Driver to perceive the world around it, make the right decision for every situation, and deliver people safely to their destinations. We think deeply and solve complex technical challenges in areas like robotics, perception, decision-making and deep learning, while collaborating with hardware and systems engineers. If you're a software engineer or researcher who's curious and passionate about Level 4 autonomous driving, we'd like to meet you. The Sensor Foundations Team's purpose is to provide cleaned-up sensor data through highly optimized APIs to Perception models, to abstract sensor hardware differences where possible, and to provide low-level Perception signals either through algorithms or machine learning. Projects on our team typically require a diverse skill set, including robotics, system integration, code optimization, and machine learning. We have a good understanding of the hardware (both sensors and compute) and the overall Perception system. The Optimization sub-team uses our know-how of CPUs, GPUs, and clever algorithms to process Waymo's sensor data super-fast and feed it to the Perception ML models. We specialize in low-level understanding of compute hardware, and we apply that knowledge wherever we can, throughout the whole stack. We are looking for a Tech-Lead Manager with a CPU, GPU, or system-level optimization background to lead this small team of Software Engineers. Depending on your prior experience, you may also be responsible for system-level optimization and be a steward of our compute resources. This role follows a hybrid work schedule and reports to the TLM of the Sensor Foundations team. You will: Lead a small team of optimization experts Identify system-level optimization opportunities Optimize existing CPU code Write and review CUDA code Collaborate with ML practitioners to understand their input-processing needs. Be a steward of our compute resources You have: B.Sc in Computer Science, Mathematics or a related field 8+ years of industry experience Strong C++ programming skills Experience with optimizing CPU or GPU code (ideally both) Prior people management experience We prefer: M.Sc or PhD in Computer Science, Mathematics or a related field Experience with system-level optimization Experience with compiler technology. The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $298,000-$368,000 USD