Top Tech Jobs & Startup Jobs in San Francisco Bay Area, CA

Leads product management for Capital One’s Consumer and Developer Experience organization. Oversees strategic pillars including developer experience, AI tools and platforms, marketing and messaging delivery, experience platforms, and enterprise supplier and operations products. Drives customer-centered product strategy, technology-enabled innovation, business outcomes, cross-functional alignment, and transformational leadership across consumer-facing digital products and enterprise platforms.

Design, build, deploy, scale, and monitor production machine learning systems. Develop models, application code, data pipelines, cloud architectures, automated tests, and CI/CD processes. Collaborate with Product and Data Science teams, ensure high availability and performance, govern models for risk and responsible AI, and lead teams developing ML solutions.

Design, develop, deploy, and support foundational AI systems, including model training, LLM inference, similarity search, guardrails, evaluation, governance, experimentation, and observability. Optimize large-scale AI systems for performance, scalability, latency, throughput, hardware utilization, and cost. Shape the technical vision and roadmap for foundational AI platforms while collaborating with engineers, research scientists, technical program managers, and product managers. Lead technical innovation and influence cross-functional stakeholders.

Leads product management for Consumer and Developer Experience, bringing Product, Technology, and Design together to build scalable digital products and platforms. Oversees strategic pillars including AI and developer tools, communication delivery, experience platforms, and enterprise supplier and operations products. Translates customer needs and business strategy into technology-driven solutions, leads cross-functional teams, manages product risks, and drives organizational alignment and growth.

Leads product strategy and strategic initiatives for Consumer and Developer Experience, partnering with senior leaders, engineering, and cross-functional teams. Responsibilities include solving complex business problems, driving AI transformation, conducting quantitative and qualitative analysis, developing innovation roadmaps and prototypes, leading strategy and product teams, fostering customer-centric culture, and building organizational alignment. The role requires strong strategic judgment, communication, relationship-building, people leadership, and product orientation.

Lead data engineering role responsible for designing, developing, testing, implementing, and supporting cloud-based data solutions. The position uses Python, Java, Scala, SQL, distributed computing, streaming technologies, data warehouses, NoSQL databases, and public cloud platforms. Responsibilities include collaborating with Agile and product teams, building scalable systems, conducting code reviews and unit tests, optimizing performance, tracking technology trends, and mentoring engineers.

Leads the design, development, deployment, and maintenance of machine learning systems at scale. Responsibilities include building ML models and data pipelines, writing production code, optimizing cloud architectures, automating testing and deployment, monitoring and retraining models, and ensuring performance, governance, security, responsible AI, and explainability. The role collaborates with Product and Data Science teams in an Agile environment focused on enterprise AI coding tools.

Conduct applied AI research and build foundation models through design, training, evaluation, validation, and production implementation. Collaborate with data scientists, software and machine learning engineers, and product managers to deliver scalable AI products. Research large deep learning models, optimization, self-supervised learning, robustness, explainability, and fine-tuning, while translating technical findings into business outcomes and pursuing an independent research agenda.

Lead the design, development, deployment, and support of scalable AI platform components, including foundation model training, LLM inference, similarity search, guardrails, evaluation, governance, experimentation, and observability. Optimize AI training and inference for latency, throughput, cost, and hardware utilization. Partner with engineering, research, product, and program teams while contributing to technical strategy and mentoring stakeholders.

Lead the design, development, deployment, and support of foundational AI systems, including LLM inference, model training, similarity search, guardrails, evaluation, governance, and observability. Drive build-versus-buy decisions, optimize production AI systems for scalability, cost, latency, and throughput, and shape long-term technical roadmaps. Manage, mentor, and grow an engineering team while partnering with scientists, product managers, and technical program managers.