Ginas Tech Jobs
San Francisco, California
Job Description Job Description Job Description Principal Machine Learning Engineer, Artificial Intelligence (AI) Required, Work From Home As a Principal Machine Learning Engineer, you are a deep technical authority responsible for designing and evolving the most critical ML systems in the company. The Principal Machine Learning Engineer will operate across training, inference, evaluation, and infrastructure, solving the hardest architectural and performance problems. While Technical Leads may own execution at the team level, you set the technical standard and shape how ML systems are built across the organization. This is a hands-on, high-impact role focused on depth. This position is 100% Remote. Principal Machine Learning Engineer Responsibilities: - Architect and build large-scale ML systems spanning data, training, evaluation, inference, and deployment. - Design reproducible, high-performance training pipelines across GPU infrastructure. - Architect inference systems that balance latency, throughput, cost, and reliability at scale. - Design and maintain data systems for high-quality synthetic and real-world training data. - Implement evaluation pipelines covering performance, robustness, safety, and bias, in partnership with research leadership. - Own production deployment, including GPU optimization, memory efficiency, latency reduction, and scaling policies. - Collaborate closely with application engineering to integrate ML systems cleanly into backend, mobile, and desktop products. - Make pragmatic trade-offs and ship improvements quickly, learning from real usage. - Work under real production constraints: latency, cost, reliability, and safety Principal Machine Learning Engineer Outcomes: - ML systems (training, inference, evaluation) are reliable, scalable, and meet defined performance targets. - Models deployed to production achieve measurable quality improvements and meet user-impact goals. - Production issues are proactively monitored, debugged, and resolved with clear root-cause analysis. - Team and cross-functional collaborators benefit from clear guidance, best practices, and scalable ML solutions. - Research-to-production cycles are efficient, safe, and continuously improve the product experience. Qualifications Principal Machine Learning Engineer Qualifications: - Strong background in deep learning and transformer-based architectures. - Artificial Intelligence (AI) experience required. - Hands-on experience training, fine-tuning, or deploying large-scale ML models in production. - Proficiency with at least one modern ML framework (e.g. PyTorch, JAX), and ability to learn others quickly. - Experience with distributed training and inference frameworks (e.g. DeepSpeed, FSDP, Megatron, ZeRO, Ray). - Strong software engineering fundamentals; you write robust, maintainable, production-grade systems. - Experience with GPU optimization, including memory efficiency, quantization, and mixed precision. - Comfort owning ambiguous, zero-to-one ML systems end-to-end. - A bias toward shipping, learning fast, and improving systems through iteration. - Experience with LLM inference frameworks such as vLLM, TensorRT-LLM, or FasterTransformer. - Contributions to open-source ML or systems libraries. - Background in scientific computing, compilers, or GPU kernels. - Experience with RLHF pipelines (PPO, DPO, ORPO). - Experience training or deploying multimodal or diffusion models. - Experience with large-scale data processing (Apache Arrow, Spark, Ray). Benefits include medical insurance, Dental, Vision, Savings Plan Options, PTO, etc. Looking to hire a Principal Machine Learning Engineer in San Francisco, CA or in other cities? Our IT recruiting agencies and staffing companies can help. We help companies that are looking to hire Principal Machine Learning Engineers for jobs in San Francisco, California and in other cities too. Please contact our IT recruiting agencies and IT staffing companies today! Additional Information Please check out all of our jobs at .
Job Description Job Description Job Description Principal Machine Learning Engineer, Artificial Intelligence (AI) Required, Work From Home As a Principal Machine Learning Engineer, you are a deep technical authority responsible for designing and evolving the most critical ML systems in the company. The Principal Machine Learning Engineer will operate across training, inference, evaluation, and infrastructure, solving the hardest architectural and performance problems. While Technical Leads may own execution at the team level, you set the technical standard and shape how ML systems are built across the organization. This is a hands-on, high-impact role focused on depth. This position is 100% Remote. Principal Machine Learning Engineer Responsibilities: - Architect and build large-scale ML systems spanning data, training, evaluation, inference, and deployment. - Design reproducible, high-performance training pipelines across GPU infrastructure. - Architect inference systems that balance latency, throughput, cost, and reliability at scale. - Design and maintain data systems for high-quality synthetic and real-world training data. - Implement evaluation pipelines covering performance, robustness, safety, and bias, in partnership with research leadership. - Own production deployment, including GPU optimization, memory efficiency, latency reduction, and scaling policies. - Collaborate closely with application engineering to integrate ML systems cleanly into backend, mobile, and desktop products. - Make pragmatic trade-offs and ship improvements quickly, learning from real usage. - Work under real production constraints: latency, cost, reliability, and safety Principal Machine Learning Engineer Outcomes: - ML systems (training, inference, evaluation) are reliable, scalable, and meet defined performance targets. - Models deployed to production achieve measurable quality improvements and meet user-impact goals. - Production issues are proactively monitored, debugged, and resolved with clear root-cause analysis. - Team and cross-functional collaborators benefit from clear guidance, best practices, and scalable ML solutions. - Research-to-production cycles are efficient, safe, and continuously improve the product experience. Qualifications Principal Machine Learning Engineer Qualifications: - Strong background in deep learning and transformer-based architectures. - Artificial Intelligence (AI) experience required. - Hands-on experience training, fine-tuning, or deploying large-scale ML models in production. - Proficiency with at least one modern ML framework (e.g. PyTorch, JAX), and ability to learn others quickly. - Experience with distributed training and inference frameworks (e.g. DeepSpeed, FSDP, Megatron, ZeRO, Ray). - Strong software engineering fundamentals; you write robust, maintainable, production-grade systems. - Experience with GPU optimization, including memory efficiency, quantization, and mixed precision. - Comfort owning ambiguous, zero-to-one ML systems end-to-end. - A bias toward shipping, learning fast, and improving systems through iteration. - Experience with LLM inference frameworks such as vLLM, TensorRT-LLM, or FasterTransformer. - Contributions to open-source ML or systems libraries. - Background in scientific computing, compilers, or GPU kernels. - Experience with RLHF pipelines (PPO, DPO, ORPO). - Experience training or deploying multimodal or diffusion models. - Experience with large-scale data processing (Apache Arrow, Spark, Ray). Benefits include medical insurance, Dental, Vision, Savings Plan Options, PTO, etc. Looking to hire a Principal Machine Learning Engineer in San Francisco, CA or in other cities? Our IT recruiting agencies and staffing companies can help. We help companies that are looking to hire Principal Machine Learning Engineers for jobs in San Francisco, California and in other cities too. Please contact our IT recruiting agencies and IT staffing companies today! Additional Information Please check out all of our jobs at .
Extreme Networks
Seattle, Washington
Job Description Job Description Over 50,000 customers globally trust our end-to-end, cloud-driven networking solutions. They rely on our top-rated services and support to accelerate their digital transformation efforts and deliver unprecedented progress. Become part of something big with Extreme! As a global networking leader, learn why there is no better time to join the Extreme team. Position details Title of position: Principal Machine Learning Engineer Position type: Full time Location: Seattle, WA Position reports to: Director of Software Systems Engineering Application deadline: Applications are being accepted on a rolling basis and this posting will remain open until filled. Work authorization: We are unable to sponsor or take over sponsorship of an employment visa, including H-1B visas, at this time About the Position: Position : Principal Machine Learning Engineer -Gen AI, Machine Learning, Graph ML, Big Data Experience : 10+ Years Seattle, WA - Hybrid Our AI Core group is pioneering platforms and solutions for Generative AI, including AI Agents, RAG, Knowledge Bases, Data Mining, Anomaly Detection, and LLM fine-tuning. These innovations power flagship Extreme products while enabling entirely new offerings. Together, we are driving a fundamental shift in how businesses manage networks by building intelligent, high-performance multi-agent systems that perceive, learn, and act in real time. At Extreme, innovation is not just encouraged, it is expected. Advance with us and help shape the future of network intelligence. Required Skills & Expertise: Degree in mathematics/computer science or related discipline. 10+ years of experience in the complete software development lifecycle including design, coding, code reviews, testing, build processes, deployments and operations. 6+ years of experience in Python with an in-depth knowledge of its advanced features and libraries. Expertise in designing RESTful APIs with hands-on experience with technologies such as FastAPI. Proficient in Docker, Kubernetes, and modern CI/CD practices. 4+ years of experience in leading the design and architecture of large distributed systems preferably on cloud platforms (e.g., AWS, Azure, Google Cloud). Experience as a mentor, tech lead or leading an engineering team. Preferred Qualifications: MS or PhD in Computer Science or equivalent experience in ML. Experience working with ML technologies (PyTorch, Sagemaker, Triton, TensorRT, etc.). Experience with NoSQL and document databases. Proven ability to handle big data, optimize workflows, and improve system performance. Come work with a team of highly talented engineers, and advance with us to achieve new heights every day! Equal Employment Opportunity Extreme Networks, Inc. is an Equal Opportunity Employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran. We are committed to taking affirmative action to employ and advance in employment qualified protected veterans, including disabled veterans, recently separated veterans, active-duty wartime or campaign badge veterans, and Armed Forces service medal veterans. Extreme Networks also strives to prevent other, subtler forms of inappropriate behavior (for example, stereotyping) from ever gaining a foothold in our organization. Whether blatant or hidden, barriers to success have no place at Extreme Networks. We encourage people from underrepresented groups to apply. This role offers a market competitive salary with an anticipated base compensation range of 150,000 to 200,000 USD. Actual compensation will depend on the selected candidate's experience, qualifications, skills, and work location. The posted range reflects the amount Extreme Networks reasonably and in good faith expects to pay upon hire. This range is determined using objective, gender neutral criteria based on skills, experience, responsibility, and working conditions. In addition to base pay, this role is eligible for a performance based bonus and the full benefits package described below. Benefits and total rewards: Extreme Networks offers a comprehensive benefits package. Specific benefits vary by country and may include: Medical, dental, and vision insurance Flexible work schedules and work-from-home opportunities where role permits Paid time off, including open time off in eligible markets and statutory leave in all markets Paid holidays in accordance with local practice Retirement savings programs, including RRSP matching in Canada Employee Stock Purchase Program, where eligible Employee assistance program Tuition reimbursement, where eligible Benefits eligibility is based on country of employment, role, and employment status. Complete benefits details will be provided during the interview process and in the formal offer of employment. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
Job Description Job Description Over 50,000 customers globally trust our end-to-end, cloud-driven networking solutions. They rely on our top-rated services and support to accelerate their digital transformation efforts and deliver unprecedented progress. Become part of something big with Extreme! As a global networking leader, learn why there is no better time to join the Extreme team. Position details Title of position: Principal Machine Learning Engineer Position type: Full time Location: Seattle, WA Position reports to: Director of Software Systems Engineering Application deadline: Applications are being accepted on a rolling basis and this posting will remain open until filled. Work authorization: We are unable to sponsor or take over sponsorship of an employment visa, including H-1B visas, at this time About the Position: Position : Principal Machine Learning Engineer -Gen AI, Machine Learning, Graph ML, Big Data Experience : 10+ Years Seattle, WA - Hybrid Our AI Core group is pioneering platforms and solutions for Generative AI, including AI Agents, RAG, Knowledge Bases, Data Mining, Anomaly Detection, and LLM fine-tuning. These innovations power flagship Extreme products while enabling entirely new offerings. Together, we are driving a fundamental shift in how businesses manage networks by building intelligent, high-performance multi-agent systems that perceive, learn, and act in real time. At Extreme, innovation is not just encouraged, it is expected. Advance with us and help shape the future of network intelligence. Required Skills & Expertise: Degree in mathematics/computer science or related discipline. 10+ years of experience in the complete software development lifecycle including design, coding, code reviews, testing, build processes, deployments and operations. 6+ years of experience in Python with an in-depth knowledge of its advanced features and libraries. Expertise in designing RESTful APIs with hands-on experience with technologies such as FastAPI. Proficient in Docker, Kubernetes, and modern CI/CD practices. 4+ years of experience in leading the design and architecture of large distributed systems preferably on cloud platforms (e.g., AWS, Azure, Google Cloud). Experience as a mentor, tech lead or leading an engineering team. Preferred Qualifications: MS or PhD in Computer Science or equivalent experience in ML. Experience working with ML technologies (PyTorch, Sagemaker, Triton, TensorRT, etc.). Experience with NoSQL and document databases. Proven ability to handle big data, optimize workflows, and improve system performance. Come work with a team of highly talented engineers, and advance with us to achieve new heights every day! Equal Employment Opportunity Extreme Networks, Inc. is an Equal Opportunity Employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran. We are committed to taking affirmative action to employ and advance in employment qualified protected veterans, including disabled veterans, recently separated veterans, active-duty wartime or campaign badge veterans, and Armed Forces service medal veterans. Extreme Networks also strives to prevent other, subtler forms of inappropriate behavior (for example, stereotyping) from ever gaining a foothold in our organization. Whether blatant or hidden, barriers to success have no place at Extreme Networks. We encourage people from underrepresented groups to apply. This role offers a market competitive salary with an anticipated base compensation range of 150,000 to 200,000 USD. Actual compensation will depend on the selected candidate's experience, qualifications, skills, and work location. The posted range reflects the amount Extreme Networks reasonably and in good faith expects to pay upon hire. This range is determined using objective, gender neutral criteria based on skills, experience, responsibility, and working conditions. In addition to base pay, this role is eligible for a performance based bonus and the full benefits package described below. Benefits and total rewards: Extreme Networks offers a comprehensive benefits package. Specific benefits vary by country and may include: Medical, dental, and vision insurance Flexible work schedules and work-from-home opportunities where role permits Paid time off, including open time off in eligible markets and statutory leave in all markets Paid holidays in accordance with local practice Retirement savings programs, including RRSP matching in Canada Employee Stock Purchase Program, where eligible Employee assistance program Tuition reimbursement, where eligible Benefits eligibility is based on country of employment, role, and employment status. Complete benefits details will be provided during the interview process and in the formal offer of employment. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.