Machine Learning Jobs in Oakland, CA

Lead the development of a compiler stack and GPU kernels for a custom dependently typed language targeting symbolic AI models, collaborating closely with researchers and mathematicians.

As a Sales Executive, you will hunt for new clients, manage enterprise accounts, and create revenue streams while collaborating with internal teams.

The AI Engineer will develop and iterate on AI models for user personalization, query understanding, and content discovery while collaborating with cross-functional teams.

Design and deploy algorithms for aircraft and obstacle detection using deep learning and geometric vision, ensuring safe autonomous navigation for drones.

Lead the Machine Learning team to develop AI systems for public sector. Provide technical direction, mentor engineers, and ensure operational excellence while collaborating with stakeholders.

The Sr. Machine Learning Engineer at Unity will design and implement auto-bidding algorithms, ensuring systems meet performance goals while leading project execution and collaborating with stakeholders.

The Solutions Architect for AI/ML at Snowflake will advise clients on best practices for Data Science workloads, design solutions, and build ML pipelines. Responsibilities also include working hands-on with SQL and Python, maintaining technical expertise and collaborating with teams to improve products.

Lead the design and implementation of enterprise-scale AI/ML solutions on Azure and AWS, ensuring security, scalability, and performance. Collaborate with teams to optimize workloads and integrate solutions with data platforms.

Develop and optimize 3D graphics algorithms for sensor simulation, leveraging GenAI/ML techniques. Collaborate with various teams to enhance simulation realism and generate high fidelity data.

Manage the ML Training Platform at Zoox, leading a team to innovate in ML practices and drive model training for autonomous vehicle technology.

Responsible for designing and implementing reinforcement learning algorithms, conducting experiments, and optimizing models for robotic applications, collaborating with multiple teams.

As Engineering Manager, ML, lead and mentor a team of ML engineers, drive technical execution, and ensure delivery of AI solutions while shaping team culture and best practices.

As the first Developer Advocate at Encord, you will educate the community, create technical content, and engage in ML/CV networks and events.

Design and build production systems for AI inference, optimize runtime services, and collaborate on AI solutions with researchers and engineers.

Design and build scalable, fault-tolerant machine learning systems while collaborating with researchers and ensuring system health through monitoring.

Develop systems and APIs for LLM inference and fine-tuning. Design production systems, collaborate with teams, and improve system efficiency.

The MLOps engineer will develop systems for LLMs, work on production ML systems, and collaborate across teams on deployment and automation.

Develop machine learning algorithms for smart buildings focusing on image processing, pose estimation, and smart IoT sensors in collaboration with product teams.

Drive the roadmap for AI and ML initiatives, manage cross-functional teams, and present product strategies while ensuring alignment on metrics and outcomes.

The Staff ML Engineer will architect scalable ML systems, leverage LLMs, and drive ML innovations to enhance user connections on Grindr.

As a Staff Software Engineer, you'll architect and build the ML platform infrastructure, guiding AI initiatives and mentoring engineers while enhancing the AI/ML stack for scalable performance.

Lead and mentor the data science team, define research roadmaps, prototype NLP architectures, and engage with industry audiences.

Lead Knowledge Graph projects from design to deployment, integrating AI systems, and managing cross-functional teams while developing and optimizing graph databases.

Design and implement machine learning algorithms for robotic manipulation, focusing on RL and IL. Collaborate across disciplines to ensure integration and successful deployment.

The candidate will design and optimize APIs and systems for ML workflows, focusing on scalability, operational rigor, and innovative solutions.