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Principal AI Research Scientist, Research Director - AI Scaling P-1227 About Databricks AI At Databricks, we are obsessed with enabling data teams to solve the world's toughest problems, from security threat detection to cancer drug development, by building and running the world's best data and AI platform. The Databricks AI Research organization enables companies to develop AI models and agents using their own data, with technologies ranging from post-training open source LLMs to developing advanced multi-agent architectures. Databricks AI is committed to the belief that a company's AI models and agents are just as valuable as any other core IP, and that high-quality AI should be available to all. About the Scaling Research Team The Databricks AI Scaling team focuses on pushing the boundaries of large language model (LLM) training and inference efficiency beyond what is required to support existing models. The team explores novel avenues for scaling and efficiency improvements across algorithms, systems, and infrastructure, requiring researchers who can both drive independent research agendas and dive deep into low level implementation details with engineering partners. Role Summary As a Principal Research Scientist - AI Scaling, you will lead a team of world class researchers and engineers to advance the state of the art in large scale machine learning, focusing on post-training, RL and inference efficiency, optimization, and scaling. You will define and execute a research roadmap that advances the Databricks AI platform and delivers tangible improvements to how customers train, serve, and adapt LLMs at scale, working closely with product, data, and engineering leaders to bring cutting edge methods into production. The Impact You Will Have Lead and grow a multidisciplinary research team focused on foundational and applied AI problems, with a particular emphasis on LLM scaling, efficiency, and systems performance. Define the scaling research roadmap in alignment with Databricks' strategic objectives, prioritizing advances in foundation model efficiency and large scale training and inference. Drive algorithmic innovations for large scale neural network training and inference, including novel optimizers, low precision techniques, and model adaptation methods, and guide your team in rigorous empirical validation against state of the art approaches. Optimize end to end ML systems for distributed training and RL, memory efficiency, and compute efficiency through close collaboration with core systems and platform teams, ensuring that research ideas translate into performant, reliable infrastructure. Partner with product and engineering to translate research breakthroughs, especially around scaling and efficiency, into customer impacting capabilities in the Databricks AI platform. Foster a culture of scientific excellence and openness, including high quality research practices, reproducible experimentation, and effective internal knowledge sharing across Databricks AI. Represent Databricks AI research externally through top tier publications, conference talks, and collaborations with academia and the open source community, with a focus on optimization and efficiency for large scale models. Mentor and develop talent, providing both technical guidance (research agendas, experimentation, implementation) and career development support for research scientists and engineers. What You Will Do Define and lead independent research programs onfoundation model efficiency, covering topics such as optimizer design, low precision training/inference, scalable model architectures, and efficient adaptation methods. Oversee the design and execution of large scale experiments, including benchmarking against state of the art methods and evaluating trade offs in quality, latency, throughput, and cost. Work hands on with your team on high quality, efficient code in Python and PyTorch for research implementation, rapid prototyping, and integration with Databricks' production systems. Collaborate with distributed systems and infra teams to push the limits of distributed training , parallelism strategies, memory management, and hardware utilization for LLMs and other large models. Establish metrics, evaluation protocols, and best practices for scaling focused research (e.g., training efficiency, inference cost, energy usage) and drive their adoption across Databricks AI. Champion responsible and robust deployment of scaling innovations, ensuring that model behavior, reliability, and safety remain first class considerations. What We Look For Proven ability to lead a research team to develop novel techniques for foundation model efficiency and related topics, with a strong track record of industry impact. Deep expertise in at least one of: generative AI, LLMs, distributed ML systems, model optimization, or responsible AI, with a strong emphasis on scaling and efficiency for large scale neural networks. Hands on leadership - strong programming skills and demonstrated ability to write high quality, efficient code in Python and PyTorch for research implementation and experimentation. Demonstrated ability to translate research innovation into scalable product capabilities in partnership with product and engineering teams. Excellent communication, leadership, and stakeholder management skills, with experience influencing cross functional roadmaps and aligning research with business impact. Nice to Have Prior work at the intersection of systems and ML, such as distributed training frameworks, compiler and kernel optimization for deep learning workloads, or memory /compute efficient model design. Strong industry and academic network in large scale ML, with ongoing collaborations or service (e.g., PC/area chair) at top conferences in ML and systems. A strong record of research impact-such as first author publications at top ML/systems conferences (e.g., ICLR, ICML, NeurIPS, MLSys), influential open source contributions, or widely used deployed systems-especially in optimization or efficiency. Pay Range Transparency Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here. Local Pay Range $270,000-$340,000 USD About Databricks Databricks is the Data and AI company. More than 20,000 organizations worldwide - including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 - rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram. Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here. Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.

Principal AI Research Scientist, Research Director - AI Scaling P-1227 About Databricks AI At Databricks, we are obsessed with enabling data teams to solve the world's toughest problems, from security threat detection to cancer drug development, by building and running the world's best data and AI platform. The Databricks AI Research organization enables companies to develop AI models and agents using their own data, with technologies ranging from post-training open source LLMs to developing advanced multi-agent architectures. Databricks AI is committed to the belief that a company's AI models and agents are just as valuable as any other core IP, and that high-quality AI should be available to all. About the Scaling Research Team The Databricks AI Scaling team focuses on pushing the boundaries of large language model (LLM) training and inference efficiency beyond what is required to support existing models. The team explores novel avenues for scaling and efficiency improvements across algorithms, systems, and infrastructure, requiring researchers who can both drive independent research agendas and dive deep into low level implementation details with engineering partners. Role Summary As a Principal Research Scientist - AI Scaling, you will lead a team of world class researchers and engineers to advance the state of the art in large scale machine learning, focusing on post-training, RL and inference efficiency, optimization, and scaling. You will define and execute a research roadmap that advances the Databricks AI platform and delivers tangible improvements to how customers train, serve, and adapt LLMs at scale, working closely with product, data, and engineering leaders to bring cutting edge methods into production. The Impact You Will Have Lead and grow a multidisciplinary research team focused on foundational and applied AI problems, with a particular emphasis on LLM scaling, efficiency, and systems performance. Define the scaling research roadmap in alignment with Databricks' strategic objectives, prioritizing advances in foundation model efficiency and large scale training and inference. Drive algorithmic innovations for large scale neural network training and inference, including novel optimizers, low precision techniques, and model adaptation methods, and guide your team in rigorous empirical validation against state of the art approaches. Optimize end to end ML systems for distributed training and RL, memory efficiency, and compute efficiency through close collaboration with core systems and platform teams, ensuring that research ideas translate into performant, reliable infrastructure. Partner with product and engineering to translate research breakthroughs, especially around scaling and efficiency, into customer impacting capabilities in the Databricks AI platform. Foster a culture of scientific excellence and openness, including high quality research practices, reproducible experimentation, and effective internal knowledge sharing across Databricks AI. Represent Databricks AI research externally through top tier publications, conference talks, and collaborations with academia and the open source community, with a focus on optimization and efficiency for large scale models. Mentor and develop talent, providing both technical guidance (research agendas, experimentation, implementation) and career development support for research scientists and engineers. What You Will Do Define and lead independent research programs onfoundation model efficiency, covering topics such as optimizer design, low precision training/inference, scalable model architectures, and efficient adaptation methods. Oversee the design and execution of large scale experiments, including benchmarking against state of the art methods and evaluating trade offs in quality, latency, throughput, and cost. Work hands on with your team on high quality, efficient code in Python and PyTorch for research implementation, rapid prototyping, and integration with Databricks' production systems. Collaborate with distributed systems and infra teams to push the limits of distributed training , parallelism strategies, memory management, and hardware utilization for LLMs and other large models. Establish metrics, evaluation protocols, and best practices for scaling focused research (e.g., training efficiency, inference cost, energy usage) and drive their adoption across Databricks AI. Champion responsible and robust deployment of scaling innovations, ensuring that model behavior, reliability, and safety remain first class considerations. What We Look For Proven ability to lead a research team to develop novel techniques for foundation model efficiency and related topics, with a strong track record of industry impact. Deep expertise in at least one of: generative AI, LLMs, distributed ML systems, model optimization, or responsible AI, with a strong emphasis on scaling and efficiency for large scale neural networks. Hands on leadership - strong programming skills and demonstrated ability to write high quality, efficient code in Python and PyTorch for research implementation and experimentation. Demonstrated ability to translate research innovation into scalable product capabilities in partnership with product and engineering teams. Excellent communication, leadership, and stakeholder management skills, with experience influencing cross functional roadmaps and aligning research with business impact. Nice to Have Prior work at the intersection of systems and ML, such as distributed training frameworks, compiler and kernel optimization for deep learning workloads, or memory /compute efficient model design. Strong industry and academic network in large scale ML, with ongoing collaborations or service (e.g., PC/area chair) at top conferences in ML and systems. A strong record of research impact-such as first author publications at top ML/systems conferences (e.g., ICLR, ICML, NeurIPS, MLSys), influential open source contributions, or widely used deployed systems-especially in optimization or efficiency. Pay Range Transparency Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here. Local Pay Range $270,000-$340,000 USD About Databricks Databricks is the Data and AI company. More than 20,000 organizations worldwide - including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 - rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram. Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here. Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. About Okta for AI Agents Okta secures access for 20,000 organizations and billions of users. Okta for AI Agents extends that work to the agentic shift. Deploying an AI agent is not like deploying traditional software. You are putting professional work output into production, and it needs deep integration, continuous tuning, and change management. Every agent needs an identity, a scope, an audit trail, and a way to be shut down when it goes wrong. Most enterprises have not built this yet. We are. We hire builders who see the cracks in enterprise agent identity that everyone else has learned to live with. The Role You are the most senior technical field authority for agent identity at Okta. Where a Senior FDE owns the outcome inside one account, you own the patterns that every account and every FDE inherits. You take the hardest and most strategic deployments yourself, set the reference architecture the team builds from, and turn what the field learns into the direction the product takes. You still write code. You also multiply the people around you, and you are the person product and engineering leadership call when an agent identity problem has no precedent. Responsibilities Own the reference architecture. Define the canonical agent identity, delegation, audit, and kill-switch patterns that Senior FDEs deploy across the portfolio, and keep them current as the standards and the product move. Lead the hardest accounts. Personally own the most strategic, regulated, or technically novel deployments, the ones where there is no playbook yet. Raise the technical bar. Review other FDEs' architectures, coach senior customer engineers and your own team, and set the standard for what good looks like in the field. Shape the roadmap. Synthesize patterns across every account into a clear point of view, and work directly with product and engineering leadership to prioritize what ships next. Represent Okta as a technical authority. Brief CISO, CIO, and Chief AI Officer audiences, contribute to the standards and frameworks shaping agent identity, and carry the external technical voice. Resolve what others cannot. Step into the hardest technical and political situations across accounts and find the path forward. Set the standard for evals and observability. Define how the team measures authorization latency, scope sprawl, delegation anomalies, audit completeness, and kill-switch verification, so it scales beyond any single customer. Build the team's leverage. Turn recurring field work into reusable modules, internal tooling, and enablement so the whole FDE function moves faster. Requirements Engineering depth. 10+ years shipping production software, with deep distributed systems and identity experience and a track record of staying hands-on while setting direction. Authority-level identity protocols. OAuth 2.0, OIDC, SAML, SCIM, RFC 8693 token exchange, act claims, CIMD and DCR, DPoP. Contribution to standards or open source is a plus. Deep agent security fluency. OWASP Top 10 for Agentic Applications, NIST AI RMF, MITRE ATLAS, plus MCP, A2A, ISO/IEC 42001, and the EU AI Act, with the judgment to apply them in HIPAA, FedRAMP, and SOC 2 environments. Expert fine-grained authorization. ReBAC and ABAC with policy engines (OPA, Cedar, OpenFGA, or equivalent), and command of the design tradeoffs at scale. Proven AI hands-on. Production integrations across the major agent platforms and MCP, and daily AI-native development. Force multiplier. A record of setting technical direction across multiple teams or accounts, and of mentoring senior engineers. Customer-facing authority. Credible from the IDE to the boardroom, trusted by CISOs and principal engineers alike, and steady when account politics get sharp. High agency, founder's mindset. Applied to building a function, not just an account. Ability to travel ( on occasion internationally) up to 35% (P25253_) The OTE range for this position for candidates located in the San Francisco Bay area is between: $269,000-$369,000 USD Below is the annual On Target Compensation (OTE) range for candidates located in California (excluding San Francisco Bay Area), Colorado, Illinois, New York and Washington. Your actual OTE, which is inclusive of base salary and incentive compensation, will depend on factors such as your skills, qualifications, experience, and work location. In addition, Okta offers equity (where applicable) and benefits, including health, dental and vision insurance, 401(k), flexible spending account, and paid leave (including PTO and parental leave) in accordance with our applicable plans and policies. To learn more about our Total Rewards program please visit: The annual OTE range for this position for candidates located in California (excluding San Francisco Bay Area), Colorado, Illinois, New York, and Washington is between: $240,000-$360,000 USD The Okta Experience Supporting Your Well-Being Driving Social Impact Developing Talent and Fostering Connection + Community We are intentional about connection. Our global community, spanning over 20 offices worldwide, is united by a drive to innovate. Your journey begins with an immersive, in-person onboarding experience designed to accelerate your impact and connect you to our mission and team from day one. Okta is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, ancestry, marital status, age, physical or mental disability, or status as a protected veteran. We also consider for employment qualified applicants with arrest and convictions records, consistent with applicable laws. If reasonable accommodation is needed to complete any part of the job application, interview process, or onboarding please use this Form to request an accommodation. Notice for New York City Applicants & Employees: Okta may use Automated Employment Decision Tools (AEDT), as defined by New York City Local Law 144, that use artificial intelligence, machine learning, or other automated processes to assist in our recruitment and hiring process. In accordance with NYC Local Law 144, if you are an applicant or employee residing in New York City, please click here to view our full NYC AEDT Notice.

Company Overview ID.me is the next-generation digital identity wallet that simplifies how individuals securely prove their identity online. Consumers can verify their identity with ID.me once and seamlessly login across websites without having to create a new login and verify their identity again. Over 152 million users experience streamlined login and identity verification with ID.me at 20 federal agencies, 45 state government agencies, and 70+ healthcare organizations. More than 600+ consumer brands use ID.me to verify communities and user segments to honor service and build more authentic relationships. ID.me's technology meets the federal standards for consumer authentication set by the Commerce Department and is approved as a NIST 800-63-3 IAL2 / AAL2 credential service provider by the Kantara Initiative. ID.me is committed to "No Identity Left Behind" to enable all people to have a secure digital identity. To learn more, visit ID.me is a full-time, in-office culture. Unless a specific job description explicitly states otherwise, all roles are on-site five days per week at one of our offices in McLean, VA; Mountain View, CA; New York City, NY; or Tampa, FL. Certain roles - such as field-based sales or other remote-by-design positions - may have different work arrangements as noted in their individual postings. At ID.me, we embrace the thoughtful use of AI tools in our daily work and there are even occasions where we leverage AI in our hiring process. However, during the interview process, we want to understand your individual skills and experiences. Therefore, we have guidelines on how AI can be appropriately used during your application and interviews which can be found here. About the Role ID.me is seeking a Principal Software Development Engineer to serve as the technical authority across the Person and Trust platforms - the systems that define who a person is and how much confidence ID.me can place in that identity. You will own the data model strategy, API contracts, and long-term architecture across the Person API, the Trust Service, and the Inspection Catalog, along with the verification and validation evidence that connects them. Person, Trust, and the Inspection Catalog are foundational systems at ID.me: together they determine who someone is, how inspection evidence is collected, and how much confidence to place in that identity. The role calls for deep expertise in data modeling and graph structures, applied to how verification and validation evidence and the resulting trust decisions are represented and queried. You will own how identity data is modeled - including how Person-to-SSN, Person-to-Face, and Person-to-Legal relationships are expressed - and how confidence in an identity is determined. You'll set technical direction, establish the patterns and contracts that other teams build against, and partner closely with Product, Architecture, Identity, Security, and Compliance to deliver a trustworthy foundation used by millions of users and trusted partners. Key Responsibilities Own the data model strategy and long-term architecture across the Person API, Trust Service, and Inspection Catalog, keeping all three as the authoritative source of truth for identity, evidence, and confidence. Own the API contracts across the domain, including versioning, compatibility, and governance standards that internal and external consumers depend on. Set technical direction and design standards for the domain. Mentor staff and senior engineers, raising the bar for data modeling, API design, and trust architecture across the organization - and filling the domain leadership gap with intentional, lasting technical ownership. Lead the modernization and consolidation of legacy identity data into a scalable, modular set of services and contracts. Ensure the security, privacy, and compliance of Person, Trust, and Inspection Catalog data. Required Qualifications 10+ years of software engineering experience, including significant time as a recognized technical authority for a complex domain spanning multiple systems. Deep expertise in data modeling and graph data structures, including designing schemas and relationships that remain correct, performant, and auditable at scale. Proven track record designing and owning APIs and data contracts for source-of-truth systems used by internal and external consumers. Demonstrated ability to set technical strategy and drive alignment across engineering teams without direct authority. Bachelor's degree in Computer Science or equivalent experience. Preferred Qualifications Especially important for this role: Hands-on experience with graph databases and the modeling tradeoffs between graph and relational representations of connected identity data - this is central to how we represent Person-to-SSN, Person-to-Face, and Person-to-Legal relationships. Experience modeling evidence and confidence scoring into a coherent, queryable record - specifically connecting inspection evidence from the Inspection Catalog to trust decisions in the Trust Service. Also valuable: Experience building or owning systems that model, store, and maintain person or entity attributes and relationships at scale. Expertise in NIST 800-63 IAL2/AAL2 standards, including evidence requirements, verification methods, and identity lifecycle management. Experience with cloud-native infrastructure (GCP, AWS, or Azure). Experience operating in regulated environments (security, compliance, or data privacy requirements). Familiarity with emerging identity and credentialing standards (e.g., Verifiable Credentials, Decentralized Identifiers, OIDC extensions). Excellent communication skills and a track record of influencing technical direction across an organization. The annual base salary listed does not include a company bonus, incentive for sales roles, equity and benefits which will be determined based on experience, skills, education, relevant training, geographic location and role. ID.me offers comprehensive medical, dental, vision, health savings account, flexible spending accounts (medical, limited purpose, dependent care, commuter benefit accounts), basic and voluntary life and AD&D insurance, 401(k) with company match, parental leave, ability to participate in unlimited paid time off subject to the terms and conditions of the PTO policy, including 8 company wide holidays, short and long-term disability insurance, accident and critical illness insurance, referral bonus policy, employee assistance program, pet insurance, travel assistant program, wellbeing and childcare discounts, benefit advocates, and a learning and development benefit. Final offers may vary from the amount listed based on qualifications, professional experiences, skills, education, relevant training, geographic location, and other job related factors. Mountain View, CA Pay Range $226,000-$296,000 USD ID.me maintains a work environment free from discrimination, where employees are treated with dignity and respect. All ID.me employees share in the responsibility for fulfilling our commitment to equal employment opportunity. ID.me does not discriminate against any employee or applicant on the basis of age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances. ID.me adheres to these principles in all aspects of employment, including recruitment, hiring, training, compensation, promotion, benefits, social and recreational programs, and discipline. In addition, ID.me's policy is to provide reasonable accommodation to qualified employees who have protected disabilities to the extent required by applicable laws, regulations and ordinances where a particular employee works. Upon request we will provide you with more information about such accommodations. Please review our Privacy Policy, including our CCPA policy, at id.me/privacy. If you provide ID.me with any personally identifiable information you confirm that you have read and agree to be bound by the terms and conditions set out in our Privacy Policy. ID.me participates in E-Verify.

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 Team & Mission: In the Oracle Perception team, our mission is to build the ultimate cognitive engine for autonomous driving. We are pioneering the use of large multimodal foundation models (e.g., Gemini) to build a powerful offboard reasoning and data flywheel system. We are moving beyond traditional perception to true scene understanding and driving actions-building offboard models that can comprehend complex driving problems, predict object/scene dynamics, and deduce driving paths with logical rationale. Our core focus is advancing the VLM foundation itself. By pushing the boundaries of multimodal pre-training and state-of-the-art post-training (SFT, RL) , we are creating models capable of rich, reasoning-based autolabeling at a massive scale. This closed-loop data engine directly powers the training and evolution of Waymo's real-time onboard models. If you are passionate about defining VLM training recipes, scaling laws, and unlocking complex reasoning via RL, this is your opportunity to redefine the foundation of autonomous driving. In this hybrid role, you will report to a Senior Staff Technical Lead Manager. You Will: Drive Pre-training & Domain Adaptation: Lead the technical strategy for curating and constructing massive-scale, high-quality multimodal pre-training datasets. Define data mixture strategies to instill deep, Waymo-specific driving intuition and physics-grounded understanding into foundation models without catastrophic forgetting. Lead Post-Training & Reasoning Enhancement: Design and implement state-of-the-art fine-tuning (SFT) and Reinforcement Learning (RLHF/RLAIF, DPO/GRPO/PPO) pipelines. Drastically improve the model's instruction-following and complex reasoning capabilities (e.g., Chain-of-Thought, spatial-temporal reasoning, and driving rationale prediction). Pioneer the VLM Data Flywheel: Architect the highly scalable inference and evaluation pipelines that leverage these trained Gemini-class models to autonomously source, sample, and autolabel critical edge cases, directly accelerating the onboard perception models. Define Training Recipes & Scaling Laws: Conduct rigorous ablation studies to optimize model architectures, token budgets, and loss functions. Establish best practices for scaling multimodal training efficiently on large GPU/TPU clusters. Drive Cross-Functional AI Strategy: Act as the principal technical visionary across ML Infra, Perception, Behavior, and AI Foundation teams. Drive consensus on the data flywheel architecture and embed VLM reasoning capabilities seamlessly into the broader autonomous vehicle stack. Provide Staff-Level Technical Leadership: Own the long-term technical roadmap for foundation model development. Mentor senior engineers, lead rigorous design reviews, and establish standard-setting engineering practices from advanced prototyping to production deployment. You Have: Master's degree in Computer Science, AI, ML, or a related technical field. 8+ years of hands-on experience designing, training, and scaling deep learning models, with at least 3+ years focused deeply on training Large Language Models (LLMs) or Vision-Language Models (VLMs) . Proven expertise in the full lifecycle of Foundation Models: from pre-training data curation (interleaved formats, tokenization) and distributed training to advanced post-training techniques. Expert-level understanding of training infrastructure and distributed paradigms (e.g., FSDP, Megatron, JAX/Pax) required for training massive models reliably. Expert-level software engineering fundamentals using Python, PyTorch, or JAX, with a track record of building reliable, highly scalable ML systems. Proven ability to operate with high ambiguity, define technical roadmaps, and drive complex, multi-quarter technical initiatives across multiple teams in a fast-paced environment. We Prefer: PhD in Computer Science, Artificial Intelligence, or a related field. Strong publication record in top-tier AI venues (e.g., NeurIPS, ICML, ICLR, CVPR) focusing on foundation models, large-scale training, reinforcement learning, or reasoning. Deep experience with advanced Reinforcement Learning paradigms applied to language or vision tasks ( focusing on improving System 2 thinking, logical deduction, and model alignment ). Demonstrated experience in Data Engineering for Foundation Models at the scale of billions/trillions of tokens (e.g., deduplication, quality filtering, synthetic data generation). Familiarity with the systemic challenges of multimodal perception in robotics or autonomous driving (e.g., 3D scene understanding, trajectory prediction). A proven track record of Staff-level impact: influencing product direction, pioneering zero-to-one ML architectures, and multiplying team efficiency through technical leadership. 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

Job Description Job Description Here at Appian, our values of Intensity and Excellence define who we are. We set high standards and live up to them, ensuring that everything we do is done with care and quality. We approach every challenge with ambition and commitment, holding ourselves and each other accountable to achieve the best results. When you join Appian, you'll be part of a passionate team dedicated to accomplishing hard things, together. Principal Applied AI Engineer Lead the engineering of software that matters - driving AI automation for the world's largest enterprises. This role is based at our h eadquarters in McLean, Virginia. Appian was built on a culture of in-person collaboration, which we believe is a key driver of our mission to be the best. Employees hired for this position are expected to be in the office 5 days a week to foster that culture and ensure we continue to thrive through shared ideas and teamwork. We believe being in the office provides more opportunities to come together and celebrate working with the exceptional people across Appian. ABOUT THE TEAM Appian Engineering spans the full depth of our platform: from the foundational layers that power enterprise scale, to the AI capabilities redefining what automation can do. We operate in a highly collaborative, fast-paced environment focused on technical precision, continuous learning, and high code quality. By joining our team, you will solve real-world problems that directly shape how Appian delivers our AI-Powered Process Automation platform to enterprises around the world. THE OPPORTUNITY As a Principal Applied AI Engineer, you will serve as the technical linchpin for applied AI on the team, bringing deep hands-on expertise in designing and operating production LLM systems and a track record of influencing engineering direction beyond your immediate scope. Equipped with cutting-edge AI tooling, you will drive the design and delivery of high-complexity AI systems - spanning code generation, agents, retrieval, structured generation, tool use, model routing, evaluation, and observability - set the technical bar for the team, and lead other engineers towards solutions of real complexity to ensure flawless Enterprise-Grade Orchestration. WHAT YOU'LL DO Develop Clean Software: Architect, build, and optimize high-performance production LLM systems while maintaining a strong personal technical presence on the team. Lead Platform Modernization: Spearhead strategic technological changes and champion code refactoring efforts to keep the core Appian codebase - and the AI systems built on it - cutting-edge, modern, and performant. Engineer with AI: Use AI coding tools fluently as a force multiplier: generating, reviewing, and critically evaluating AI-assisted code to ship faster without compromising quality or correctness. Lead Architecture & Delivery: Drive technical story breakdowns, acceptance criteria, and architectural design across complex, multi-tier and AI-powered application layers - from feature scoping through implementation. Build prototypes to de-risk novel AI approaches and establish the standards others build on. Optimize Performance & Scale: Manage product availability, latency, scalability, and efficiency by engineering deep reliability into our core software systems and performing advanced system tuning. Drive Engineering Excellence: Radiate development best practices across the department, perform meticulous code reviews on design and implementation, and build automation frameworks to prevent problem recurrence. Lead & Grow Engineers: Actively coach and mentor engineers at multiple levels, identify and close skill gaps on the team, and take ownership of accelerating the technical growth of those around you. Influence Technical Documentation: Share your expert domain knowledge regularly across the department, building a reputation as a vital resource and publishing high-quality content to Engineering's permanent documentation site. REQUIRED QUALIFICATIONS Education: Minimum of a Bachelor of Science degree in Computer Science or a related technical/analytical discipline. (Equivalent experience is not accepted in lieu of a degree). Experience: 10+ years of relevant software development experience with a BS (or 8+ years of experience paired with a Master of Science in Computer Science or related field). Production LLM Systems: Deep hands-on experience designing and operating production LLM systems. AI Systems Expertise: Demonstrated expertise across code generation, agents, retrieval, structured generation, tool use, model routing, evaluation, and observability. AI-Augmented Development: Demonstrated experience using AI coding assistants and a strong ability to evaluate, coach others on, and selectively apply AI-generated code in a production engineering context. Domain Expertise: Strong distributed-systems, API, security, and reliability foundations, with the ability to contribute meaningfully at a senior individual contributor level within that space. Cross-Team Influence: Demonstrated ability to drive technical decisions and shape engineering practices beyond a single team or project scope. Production Mastery: Proven experience developing, optimizing, and maintaining a high-volume, mission-critical production service environment. Communication & Alignment: Exceptional ability to communicate highly technical architectures verbally, visually, and in writing to diverse engineering audiences. PREFERRED QUALIFICATIONS Compilers & Program Analysis: Experience with compilers, program analysis, formal or executable specifications, or legacy modernization is strongly preferred. We value experience with enterprise platforms such as Salesforce or ServiceNow, as these skills translate well into our Enterprise-Grade Orchestration environment. The base salary range represents a good faith and reasonable estimate of the range at the time of posting. Actual compensation will be dependent on a number of factors including, but not limited to, the candidate's relevant work experience, qualifications, internal peer equity, and market and business conditions that exist when extending an offer. A discretionary bonus may be awarded in recognition of individual and company performance. In addition, Appian provides generous benefits offerings that include a 401(k) plan with company match, flexible time off, paid parental leave, medical, dental, and vision plans, life insurance, disability insurance, wellness programs, flexible spending accounts, health savings account contributions, an employee referral bonus program, and learning and development resources. Certain positions may be eligible for equity awards. Pay and benefits are subject to change at any time, consistent with the terms of any applicable compensation, commission, bonus, or benefit plans. Base Salary Range $200,000-$350,000 USD Tools and Resources Training and Development: During onboarding, we focus on equipping new hires with the skills and knowledge for success through department-specific training. Continuous learning is a central focus at Appian, with dedicated mentorship and the First-Friend program being widely utilized resources for new hires. Growth Opportunities: Appian provides a diverse array of growth and development opportunities, including our leadership program tailored for new and aspiring managers, a comprehensive library of specialized department training through Appian University, skills based training, and tuition reimbursement for those aiming to advance their education. This commitment ensures that employees have access to a holistic range of development opportunities. Community: We'll immerse you into our community rooted in respect starting on day one. Appian fosters inclusivity through our 8 employee-led affinity groups. These groups help employees build stronger internal and external networks by planning social, educational, and outreach activities to connect with Appianites and larger initiatives throughout the company. Benefits Appian offers a comprehensive benefits package designed to support your health, wellbeing, and financial future. Benefits may include health coverage, Employee Assistance Program (EAP) with free mental health support, life and disability insurance, an Employee Stock Purchase Program (ESPP), a retirement/pension plan, wellness dollars, tuition reimbursement, family-forming benefits and more. Benefits vary by country-please ask your Talent Acquisition contact for details specific to the location you are applying to. About Appian Appian provides AI automation for mission-critical work. We automate complex processes in large enterprises and governments. Our platform is known for its unique reliability and scale. We've been automating processes for more than 25 years and understand enterprise operations like no one else. For more information, visit Nasdaq: APPN Follow Appian: LinkedIn, Youtube, Instagram, Facebook Appian is an equal opportunity employer that strives to attract and retain the best talent. All qualified applicants will receive consideration for employment without regard to any characteristic protected by applicable federal, state, or local law. Appian provides reasonable accommodations to applicants in accordance with all applicable laws. If you need a reasonable accommodation for any part of the employment process . click apply for full job details

AI Engineer 5 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. Design, implement and optimize multi-model orchestration pipelines - integrating LLMs, vector search, and domain-specific models into unified systems Establish and lead cost-performance governance reviews across AI systems, tracking GPU utilization, model throughput, and inference cost efficiency Lead team design councils or design review boards to ensure technical consistency and compliance with AI engineering standards Mentor Principal and Manager-level AI engineers, fostering cross-domain learning and elevating organizational technical maturity The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 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 4 years of experience developing AI and ML algorithms or technologies At least 6 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy 7 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, delivering, and supporting complex AI systems 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 Experience architecting and integrating heterogeneous AI systems - including rule-based, retrieval-augmented, and generative components - into unified production pipelines Experience defining and enforcing standards for ethical AI deployment, including explainability, fairness, and human-in-the-loop review processes Demonstrated ability to balance model performance and operational cost through dynamic inference strategies and model compression 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: $229,900 - $262,400 for AI Engineer 5McLean, VA: $229,900 - $262,400 for AI Engineer 5New York, NY: $250,800 - $286,200 for AI Engineer 5San Jose, CA: $250,800 - $286,200 for AI Engineer 5 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 . click apply for full job details

AI Engineer 5 AI Foundations, LLM Core and Agentic AI) Overview: 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. Design, implement and optimize multi-model orchestration pipelines - integrating LLMs, vector search, and domain-specific models into unified systems Establish and lead cost-performance governance reviews across AI systems, tracking GPU utilization, model throughput, and inference cost efficiency Lead team design councils or design review boards to ensure technical consistency and compliance with AI engineering standards Mentor Principal and Manager-level AI engineers, fostering cross-domain learning and elevating organizational technical maturity The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 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 4 years of experience developing AI and ML algorithms or technologies At least 6 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy 7 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, delivering, and supporting complex AI systems 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 Experience architecting and integrating heterogeneous AI systems - including rule-based, retrieval-augmented, and generative components - into unified production pipelines Experience defining and enforcing standards for ethical AI deployment, including explainability, fairness, and human-in-the-loop review processes Demonstrated ability to balance model performance and operational cost through dynamic inference strategies and model compression 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: $229,900 - $262,400 for AI Engineer 5 McLean, VA: $229,900 - $262,400 for AI Engineer 5 New York, NY: $250,800 - $286,200 for AI Engineer 5 San Francisco, CA: $250,800 - $286,200 for AI Engineer 5 San Jose, CA: $250,800 - $286,200 for AI Engineer 5 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 . click apply for full job details

AI Engineer 5 AI Foundations, LLM Core and Agentic AI) Overview: 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. Design, implement and optimize multi-model orchestration pipelines - integrating LLMs, vector search, and domain-specific models into unified systems Establish and lead cost-performance governance reviews across AI systems, tracking GPU utilization, model throughput, and inference cost efficiency Lead team design councils or design review boards to ensure technical consistency and compliance with AI engineering standards Mentor Principal and Manager-level AI engineers, fostering cross-domain learning and elevating organizational technical maturity The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 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 4 years of experience developing AI and ML algorithms or technologies At least 6 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy 7 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, delivering, and supporting complex AI systems 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 Experience architecting and integrating heterogeneous AI systems - including rule-based, retrieval-augmented, and generative components - into unified production pipelines Experience defining and enforcing standards for ethical AI deployment, including explainability, fairness, and human-in-the-loop review processes Demonstrated ability to balance model performance and operational cost through dynamic inference strategies and model compression 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: $229,900 - $262,400 for AI Engineer 5 McLean, VA: $229,900 - $262,400 for AI Engineer 5 New York, NY: $250,800 - $286,200 for AI Engineer 5 San Francisco, CA: $250,800 - $286,200 for AI Engineer 5 San Jose, CA: $250,800 - $286,200 for AI Engineer 5 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 . click apply for full job details

Energy is the binding constraint on human progress. Solar and storage are the lowest cost sources of new generation, but the conventional project delivery model has not changed in 30 years and deployment cannot keep pace with demand. Planted is turning power plants from projects into products. Our software turns raw land into a build-ready power plant in minutes instead of months. Our hardware delivers twice the energy on every acre. Our robots put steel in the ground so output scales with production lines instead of headcount. We're looking for a technical leader to build and scale the software organization at the center of that transition - from the autonomy stack running on our robots to the AI systems that will make deployment even faster. You will own the architecture, roadmap, and team driving Planted's next phase of growth. We don't wait for abundance. We build it. About The Role Software is both the brains of our machines and the connective tissue of Planted operations. You will lead and grow a software organization spanning three domains: autonomous robotic vehicle software, our suite of web-based power plant design, build, and operate tools, and an emerging portfolio of AI agents that automate engineering, estimation, and operations workflows. We are looking for a pragmatic technical leader with a track record of building high-performing, multi-disciplinary software teams. You must be deep enough technically to drive key architectural decisions across the vertically integrated platform, and strategic enough to drive and execute on the product roadmap. You have systems literacy (e.g., how data moves from a robot's camera into an ML pipeline) and prioritize delivery mechanics over heavy-handed project management. Our robots are building projects in the field today and our design software is in front of customers. Your mandate is to scale the product and the team to support our current 10x year over year growth in megawatts deployed. The Team: You will join a group at the intersection of deep tech and massive physical infrastructure. Our engineering core brings robotics and automation DNA from SpaceX and Tesla, working directly alongside veteran energy developers. We are led by repeat founders with a successful prior exit (Cogenra to SunPower). Planted is backed by leading investors in energy and Physical AI, including Breakthrough Energy Ventures, Khosla Ventures, and Piva Capital. The annual salary range for this full-time position is $275,000-$325,000 plus a meaningful equity stake and benefits. Pay within the range is based on candidate experience, job-specific skills, and education. The target experience for the position is 10-15+ years. We work together in person 5 days/week at our HQ in Oakland, CA. KEY RESPONSIBILITIES Organizational Leadership & Talent Development: Build, scale, and mentor a high-performing, multi-level software organization, including direct management of engineering managers, principal engineers, and system architects. Foster a culture of technical excellence, accountability, and continuous growth. Recruit and retain top-tier software talent across cloud, spatial/CAD, embedded, and robotics domains while allowing technical experts to own the architecture. Strategic Execution & Stakeholder Management : Own the software roadmap and drive the predictable, on-time delivery of complex, multi-system software projects across multiple products. Set clear expectations, communicate progress, and align software deliverables. Collaborate seamlessly with the Commercial team, Hardware Engineering, and Project Operations. Make the build-vs-buy, stack, and platform decisions that will hold up at 100x scale. Software Product Suite Ownership: Lead development across our core platforms: Power Planter (automated layout, engineering, and costing), Build View (autonomous fleet management, field deployment, and QA/QC), and Operate View (inspection, operations, and maintenance tools for large-scale solar plants). Autonomous Robotic Vehicle Platforms: Lead the engineering teams deploying the full software stack across our autonomous field machine fleet (fleet logic, behavior trees, and path planning, modern and classical controls, ROS2, etc.). Data Flywheel: We operate our field machines like modern manufacturing lines. You will own the telemetry and data infrastructure that monitors production with statistical process control and turns every installation into training data for better models and improved machine productivity. AI Systems: Build the team and roadmap for AI agents that automate design, estimation, project delivery, and operations workflows, grounded in the data our robots and projects generate. QUALIFICATIONS 10 to 15+ years of software engineering experience, including 5+ years leading engineering teams (senior ICs and managers) shipping production systems. Deep expertise in full stack software development involving hardware and software integration like robotics, IoT, or industrial automation. Track record shipping robotics, autonomous vehicles, or hardtech software into the field at scale-with a strong focus on fleet reliability, continuous testing, and real-time observability. Broad leadership capability across platform/full-stack teams, cloud infrastructure, data systems, or applied AI/ML groups outside your core specialty. Systems architecture judgment with strong understanding of how technologies work together (e.g., middleware, pub/sub architectures, web services, and ML pipelines). You do not need to write the C++ on the robot, but you must understand edge compute, latency, and hardware-in-the-loop testing. PREFERRED QUALIFICATIONS Field robotics : Experience in construction, agriculture, mining, defense, logistics, or autonomous vehicles operating off-pavement (e.g., Waymo, Cruise, Bedrock Automation). DevOps & Delivery: Strong understanding of modern software deployment and containerization (Docker). Experience with CI/CD, release pipelines, and edge deployment strategies, focusing on how code reliably gets to the machine. Agentic and AI-Augmented Software Engineering: Experience building, rebuilding, and managing AI-integrated software development platforms and teams. Robotics & Controls: Familiarity with the complexities of deploying field-robotics software (e.g., ROS2, vehicle navigation, and autonomy stacks). You understand the unique delivery challenges of robotics compared to traditional software. Perception & Sensing: Experience with LiDAR, stereoscopic/IR cameras, object detection, spatial mapping, and SLAM in dynamic outdoor environments. Strong understanding of middleware, pub/sub architectures alongside web services, backend technologies, and ML pipelines. Spatial / CAD Expertise: Deep understanding of software platforms working with geospatial data (GIS, CAD engines, 3D modeling, or automated parametric design). Industrial Operations: Exposure to automated manufacturing execution systems (MES) managing statistical process control, telemetry monitoring, or fleet analytics in hardtech, renewable energy environments, or advanced manufacturing. What We Offer 11 paid company holidays and flexible Paid Time Off (PTO) Company-paid in-office lunches Stock options Medical, vision, dental, and other benefits Pre-tax commuter benefits 401(k) A chance to have an empowered, meaningful, and early role in climate How This Is A Fit You want to solve challenging problems You are biased towards action and focus on the vital work that drives the most impact You prioritize the physical and psychological safety of yourself and those around you You are humble, embrace change, and deliver and receive candid feedback You are optimistic about the future and can make tough decisions to help get there You have high expectations and coach, develop, and make time to help others Planted is an equal opportunity employer committed to growing inclusively, regardless of race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, medical condition, age, or veteran status. However you identify, or whatever background you bring with you, please apply. We look forward to hearing from you.

Karman is a fast-growing NVIDIA-backed AI company enabling AI data centers to dynamically orchestrate power and unlock more compute capacity from existing energy infrastructure. For over a decade, we have applied AI to the electric grid - bringing real-time visibility and power-flow control to complex energy infrastructure. Our Karman platform, built on a custom NVIDIA module, brings that same capability to AI data centers, giving operators a way to better use the power already available to them. We are building the Karman Digital Environment (KDE), a simulation platform that will evolve how Karman is developed, verified, and brought to market. Today, Karman is developed and verified against shared physical systems, including custom NVIDIA-based edge compute units that process sub-millisecond power waveform data and issue real-time control signals to GPU infrastructure. This is a hardware constraint that limits how fast teams can iterate. KDE will remove that constraint, enabling simulation-driven development at scale across every layer of fidelity, from rapid experimentation to high-confidence system validation. This is a technical leadership role reporting to the VP, AI & Applications, with company-wide impact across architecture, product, and customer-facing teams. Responsibilities Own the end-to-end architecture of KDE as the simulation platform for developing, testing, and validating Karman before production deployment. Architect systems spanning heterogeneous time domains - from sub-millisecond control paths to system-level orchestration - with coherent time management and deterministic behavior across both. Design and evolve the core simulation platform: time synchronization across paced (real-time SIL) and unpaced (batch) execution modes, signal routing and data flow orchestration, deterministic replay and scenario execution, and the platform APIs and data contracts consumed by algorithm, QA, product, and GTM teams. Define and maintain the platform's performance envelope - latency, jitter, throughput, and fidelity - and lead optimization across the full stack. Serve as the technical authority for simulation and validation methodology, partnering with algorithm, QA, product, hardware, firmware, and GTM teams to align platform capabilities with real-world Karman deployments. Build and lead an engineering team spanning real-time systems, simulation infrastructure, power systems modeling, and GPU calibration, while remaining deeply hands-on in architecture and critical technical decisions. Represent KDE on a standing cross-functional council with Algorithms, Product, GTM, and QA, arbitrating priorities across the platform's customers and maintaining architectural direction with senior peers. Minimum Qualifications Bachelor's or advanced degree in Electrical Engineering, Computer Engineering, Computer Science, Robotics, Physics, or a related field 10+ years in systems architecture, simulation platforms, real-time or hardware-in-the-loop systems, embedded systems, or high-performance distributed platforms Experience as a hands-on player-coach leading small, high-performing engineering teams A proven track record designing and delivering simulation platforms or large-scale test systems that other engineering teams treat as production hardware, including data ingestion, telemetry, and playback at production scale, and the ability to design platform APIs and data contracts used by multiple teams Deep expertise in system-level behavior - scheduling, concurrency, memory access patterns, latency budgets, jitter measurement, and determinism at sub-millisecond scale Substantive fluency in the physics of the simulated domain - for this role, AC power distribution, control-loop dynamics, and electrical protection systems - is sufficient to make architectural decisions independently. Candidates from adjacent domains (automotive powertrain, aerospace propulsion, grid simulation, robotics dynamics) who've reached comparable depth will also be considered Experience leading or contributing to a novel modeling problem in the platform's domain Strong communication skills, with the ability to translate complex system designs for technical and non-technical stakeholders alike Willingness to travel up to 25% of time Enhanced Qualifications (Nice to Have) Experience with GPU-based systems or other accelerators, including power and performance tradeoffs Experience in data center power infrastructure or hyperscaler energy-aware computing Familiarity with AI inference serving systems (vLLM, TensorRT-LLM, Triton) sufficient to reason about workload-driven power dynamics Salary Range: $200,000 to $240,000 base compensation depending on experience and level, plus stock options. This role spans multiple job levels; final level and compensation will be determined based on the candidate's experience. Location: This position can be performed remotely from within the United States. Preference will be given to candidates based in or around the Bay Area (CA) or Ann Arbor, MI. Periodic travel to the company's HQ in Ann Arbor, MI is required. Our Commitments: Karman values the diversity of our team. We provide equal employment opportunities without regard to race, color, religion, creed, sex, gender, sexual orientation, gender identity or expression, national origin, age, physical disability, mental disability, medical condition, pregnancy or childbirth, sexual orientation, genetics, genetic information, marital status, or status as a covered veteran or any other basis protected by applicable federal, state and local laws. We are committed to: Creating a diverse and inclusive workplace that is welcoming, supportive, affirming and respectful Empowering employees to solve problems and work together to make a difference Providing mentorship and growth opportunities as part of a collaborative team A flexible work environment with flexible paid time off Competitive compensation and benefits, including health, dental, vision, and employer-match 401k

Karman is a fast-growing NVIDIA-backed AI company enabling AI data centers to dynamically orchestrate power and unlock more compute capacity from existing energy infrastructure. For over a decade, we have applied AI to the electric grid - bringing real-time visibility and power-flow control to complex energy infrastructure. Our Karman platform, built on a custom NVIDIA module, brings that same capability to AI data centers, giving operators a way to better use the power already available to them. The VP, AI & Applications leads the intelligence layer of Karman - the algorithms, control methods, and optimization techniques that turn microsecond-resolution measurement data into closed-loop control actions and quantifiable customer value. Reporting to the Chief Technology Officer, this role owns how Karman creates value across the data center power system: the internal power distribution system, the utility connection, and ancillary loads and generation including cooling, capacitor shelves, and on-site solar plus battery. The VP partners with the VP, Engineering on the platform that runs these methods in production, and with VP, Product on how value is packaged and delivered to customers. Responsibilities Lead and set technical direction for the team responsible for Karman's algorithms, control methods, optimization, and applied research - including power flow control and closed-loop adaptive control - through direct management of a Director and Principal-level individual contributors Drive technical co-development with strategic technology partners across hardware, firmware, and commercial tracks, and provide customer-facing technical leadership, working with GTM and Product Develop and manage release plans for algorithms and applications work, with clear engineering direction, validation strategy, and tracking against committed product capabilities Partner with the VP, Engineering to ensure algorithms and control methods are designed for production deployment on the Karman software and hardware platform Stay hands-on early in the role and scale toward leader-of-leaders as the team grows Collaborate with the People Team to attract, onboard, and retain top talent in algorithms, applied AI, and control systems Optimize resource allocation, budgeting, and timelines for team effectiveness Develop and report on success metrics that measure the team's contribution to organizational objectives Minimum Qualifications 10-15+ years of professional experience leading teams that develop algorithms, control systems, optimization methods, or applied AI in production Deep technical background in one or more of: control theory, power systems, optimization, applied machine learning, or signal processing Demonstrated experience in algorithms and decision-making paradigms with edge AI tools, including control systems that run offline or isolated for extended periods Track record of developing leaders and growing the careers of senior engineers and researchers; sees mentorship and team development as a core measure of personal impact Demonstrated ability to lead a senior, technically deep team while remaining hands-on enough to shape architecture and methods directly Experience translating research and prototypes into shipped products in a startup or fast-moving environment Strong communication skills, including the ability to represent technical work credibly to executives, customers, and external technical organizations Experience with intellectual property strategy and the patent process Willingness to travel up to 20% of time Enhanced Qualifications (Nice to Have) PhD strongly preferred in Electrical Engineering, Computer Science, Control Systems, Applied Mathematics, Operations Research, or a related technical discipline Experience with energy systems, power electronics, or grid-edge applications Published research, granted patents, or recognized contributions to control systems, applied AI, or power systems Background in real-time systems, deterministic control loops, or hard real-time operating systems Experience with digital twins, hardware-in-the-loop simulation, or co-simulation environments Salary Range: $230,000 to $290,000 base compensation depending on experience plus stock options. Salary will be commensurate with an individual's skills, training, years of experience, and in line with internal compensation bands. Location: This position can be performed remotely from anywhere in the United States. Our Commitments: Karman values the diversity of our team. We provide equal employment opportunities without regard to race, color, religion, creed, sex, gender, sexual orientation, gender identity or expression, national origin, age, physical disability, mental disability, medical condition, pregnancy or childbirth, sexual orientation, genetics, genetic information, marital status, or status as a covered veteran or any other basis protected by applicable federal, state and local laws. We are committed to: Creating a diverse and inclusive workplace that is welcoming, supportive, affirming and respectful Empowering employees to solve problems and work together to make a difference Providing mentorship and growth opportunities as part of a collaborative team A flexible work environment with flexible paid time off Competitive compensation and benefits, including health, dental, vision, and employer-match 401k

Karman is a fast-growing NVIDIA-backed AI company enabling AI data centers to dynamically orchestrate power and unlock more compute capacity from existing energy infrastructure. For over a decade, we have applied AI to the electric grid - bringing real-time visibility and power-flow control to complex energy infrastructure. Our Karman platform, built on a custom NVIDIA module, brings that same capability to AI data centers, giving operators a way to better use the power already available to them. The Power Applications team takes power control and orchestration algorithms from idea to production. We own the complete end-to-end process: developing power control and orchestration algorithms, translating them into deployable applications, and owning the deployment and maintenance of those applications in the field. As the Technical Lead, Power Applications, you will coordinate data scientists and software engineers to produce these applications, define repeatable and scalable workflows that let the team deliver efficiently, and act as the technical interface to other teams on the stack. This is a leadership role. While you will still spend meaningful time in the codebase, a large part of the work is communication, coordination, and project management. Your leverage comes from the designs you set, the standards you hold, the engineers you develop, and your ability to keep cross-functional work moving. Success in this role is measured by driving continuous delivery, building for scale and resilience, and navigating the demands of a rapidly growing company. This position works cross-functionally with product, engineering, and data science teams and is open to fully remote candidates, with periodic travel expected for company retreats and key on-site engagements. Responsibilities Enable the Power Applications team to own the end-to-end lifecycle of Utilidata's power control and orchestration applications, from algorithm development, through translation into deployable software, to deployment and ongoing maintenance in production Directly contribute to the Power Applications codebase and work with the team to define and own code quality standards and engineering workflows Serve as the senior individual contributor coordinating data scientists and software engineers, aligning the group on design and quality through architecture and code review Design continuous delivery workflows that bridge algorithm development and production, including the path from prototype code (e.g., Python) to the deployed application's language (e.g., Rust), so work moves to production smoothly and repeatably Act as the technical interface between Power Applications and other teams on the stack, establishing clear system boundaries, data contracts, and power application SLAs Contribute to system architecture discussions for the Karman platform as a whole, ensuring the subsystems that support power-flow control fit coherently into that wider architecture Build for reliability and scale so power applications run continuously across experimentation, staging, and deployed environments. Minimum Qualifications 10+ years of software engineering experience, including a track record of technical leadership on complex production systems Demonstrated ability to lead engineers through architecture, code review, and mentorship, and to raise the technical bar of a team Excellent written and verbal communication skills, with substantial experience working directly with stakeholders across teams Strong project management and technical planning skills - sequencing work, managing cross-team dependencies, translating product requirements into technical designs Strong foundation in distributed systems and reliability engineering: fault tolerance, graceful degradation, observability, and testing for systems that cannot go down Experience taking software from prototype to hardened production, ideally where the platform and requirements were still evolving Proficiency in Python and at least one systems language (C++, Rust, or Go) Willingness to travel up to 10% of time Enhanced Qualifications (Nice to Have) Hands-on experience with real-time, low-latency, or control systems : software that must respond within strict time bounds and behave predictably under load Experience with edge or embedded computing, especially on NVIDIA platforms (Jetson-class devices, CUDA, or NVML) Background in power systems, energy, industrial control, robotics, or another physical-world real-time domain) Experience productionizing ML models or algorithms in collaboration with data science teams Salary Range: $180,000 to $220,000 base compensation depending on experience and level, plus stock options. This role spans multiple job levels; final level and compensation will be determined based on the candidate's experience. Location: This position can be performed remotely from anywhere in the United States. Our Commitments: Karman values the diversity of our team. We provide equal employment opportunities without regard to race, color, religion, creed, sex, gender, sexual orientation, gender identity or expression, national origin, age, physical disability, mental disability, medical condition, pregnancy or childbirth, sexual orientation, genetics, genetic information, marital status, or status as a covered veteran or any other basis protected by applicable federal, state and local laws. We are committed to: Creating a diverse and inclusive workplace that is welcoming, supportive, affirming and respectful Empowering employees to solve problems and work together to make a difference Providing mentorship and growth opportunities as part of a collaborative team A flexible work environment with flexible paid time off Competitive compensation and benefits, including health, dental, vision, and employer-match 401k

Job Description Job Description Lead / Principal Process ML Engineer Job Title: Lead / Principal Process ML Engineer Job Type: Full-time Location: San Diego, CA Summary We are building AI platforms that run on real factory floors, predicting, optimizing, and controlling manufacturing processes in real time. This role is needed to expand our process optimization capability - we need a technical leader who can own the full lifecycle of ML-driven process optimization products, from causal modeling to productization and customer deployment. Currently there is no dedicated technical lead for this product area, and growing customer demand requires a senior leader to set the technical vision and drive execution. Roles and Responsibilities Own the technical direction for key projects - set vision, define what to build, manage priorities, and be accountable for delivery Lead development of ML-driven process optimization products - from causal modeling to productization and customer deployment Make architecture decisions: select modeling approaches, define system boundaries, and evaluate trade-offs between physical fidelity, inference speed, and product constraints Define modeling strategy - decide which physics to encode, which architectures to use, and how to validate against real process data Drive architecture reviews and technical decision-making across the process optimization team Hire, mentor, and grow engineers - build a high-performing team through hiring, code reviews, and technical coaching Coordinate across HQ (Seoul) and overseas R&D labs - aligning research with product roadmaps across time zones Own production-grade delivery - models must run reliably inside equipment operating 24/7 on customer lines Requirements Doctorate (Ph.D.) Mechanical Engineering, Physics, Computer Science, Electrical Engineering, or a related field 8+ years of industry experience post-Ph.D. Proven track record of shipping process optimization or control products from problem definition through customer-facing deployment Experience leading a technical team - setting direction, managing delivery, and making architecture decisions Strong physics foundation (fluid dynamics, thermodynamics, heat transfer, mechanics) Strong ML skills (PyTorch, custom architectures, PINNs, neural operators, surrogate models) Ability to bridge physics and product - translate process understanding into model design and product features Comfort with ambiguity: able to define the problem and the approach, not just execute a spec Experience shipping ML-driven process optimization or control products in an industry setting Experience leading or managing a technical team (ML or applied science) Experience with production software systems - ML integration, data pipelines, deployment infrastructure Preferred Requirements Prior role as Tech Lead, Staff Engineer, or Team Lead in an ML or applied science team Experience productizing process optimization as a commercial product deployed on customer sites Hands-on manufacturing process experience - semiconductor, SMT, electronics assembly, or precision manufacturing Experience coordinating technical direction across distributed teams (HQ + overseas R&D) Published work in scientific machine learning, computational physics, or neural operators Experience with SPC, Cpk analysis, or 3D inspection/metrology systems Benefits • Health/Dental/Vision/Life Insurance at no employee premium (including dependent coverage) • 401K retirement plan with 5% matching • Generous PTO and paid holidays