Machine Learning Jobs in Oakland, CA

The Head of Clinical Development & Strategy will lead clinical strategy, develop product profiles for early-stage assets, and shape collaborations with pharma partners, focusing on medical necessity and strategic direction.

Lead a major product area end-to-end: set strategy and KPIs, define customer personas and market thesis, prioritize features, drive execution with engineering, and align cross-functional stakeholders to deliver high-impact AI-enabled hiring and people-analytics solutions.

Work post-sale with enterprise customers to implement and scale Labelbox data pipelines, advise on ML/LLM architecture and integrations (API, SSO, SaaS), manage onboarding and implementations, mentor users, drive product feedback and customer references, and partner with sales and product teams to realize ML goals.

As an Applied AI Engineer at Luminai, you will design experiments, optimize machine learning models, and enhance AI platforms for healthcare automation.

The Machine Learning Scientist will develop reinforcement learning algorithms for protein design, collaborate with teams, and shape machine learning strategies.

The Senior Manager, Product Lead will oversee a team of product managers, driving product strategy, talent development, and excellence in AI-powered legal products.

Lead pre-sales efforts for Media & Entertainment customers: present Snowflake to executives and technical audiences, deliver demos and POCs, design solutions, collaborate with product and engineering, and close large deals while maintaining deep industry and competitive knowledge.

Lead the Platform Software Engineering team building and scaling core data infrastructure for research, market-making, and risk platforms. Hands-on role combining individual contributor work, system architecture, cross-functional project leadership, and people management while collaborating with Research and Business Operations.

The Forward Deployed Research Scientist engages directly with AI labs to develop data strategies, fine-tune models, run experiments, and collaborate on publishing research, all in a fast-paced client-focused setting.

Build and maintain backend APIs and data pipelines that ingest and process large-scale construction data (360° video, schedules, IoT). Optimize storage and query performance using DuckDB and PostgreSQL, extend Airflow workflows, integrate Wasm for local computation, monitor data quality, and collaborate with frontend, CV, and ML teams to deploy production models and analytics.

The Applied Scientist will drive research on efficient adaptive machine learning, deploy ML systems end-to-end, and contribute to product strategy, focusing on real-world impact and innovation.

Seeking Machine Learning Systems Engineers to build end-to-end 3D native ML systems, focusing on training and inference challenges.

Lead development of scalable molecular dynamics pipelines, integrating physics-based models with machine learning frameworks to enhance molecular engineering and experimentations.

The ML Research Scientist will design Bayesian optimization frameworks, collaborate with lab scientists, and integrate ML models with experimental data.

The role involves designing de novo frameworks for molecular engineering, collaborating across teams to optimize data-driven biological experiments and integrating ML models with experimental systems.

Develop and train conditioned policies and MARL systems to simulate realistic driving behaviors, implement safety-constrained RL algorithms, design rewards and evaluation metrics, optimize large-scale training pipelines, advance neural architectures for long-horizon planning and spatial reasoning, and integrate research models with production simulation and planning teams.

Develop Cloud Data Infrastructure for Assured AI in autonomous vehicles, focusing on ML model training, evaluation, and deployment.

Develop deep learning models for autonomy applications, implement ML algorithms for self-driving vehicles, and resolve real-world testing issues.

The Software Engineer, Perception develops autonomous aircraft systems to detect and manage wildfires using real-time data processing and machine learning techniques.

Develop prototypes, PoCs, and MVPs for GenAI solutions. Apply deep learning and ML principles using Python, Hugging Face, LangChain, OpenAI API, TensorFlow/Keras/PyTorch, and cloud model services. Work with multi-modal data and intelligent agent tools. Be self-motivated, collaborative, and focused on solving hard AI/GenAI problems.

The Senior ML/RL Engineer will develop behavior models, implement RL algorithms focusing on safety, design reward functions and optimize training environments while collaborating across teams.

Develop and deploy manufacturing intelligence systems and machine learning models to enhance operational efficiency in production environments, collaborating across teams to achieve impactful solutions.

Build and automate large-scale ML data pipelines and tooling for autonomous trucking. Improve dataset curation, deduplication, labeling, evaluation, and metrics infrastructure. Collaborate with robotics, autonomy, and infra teams to support continuous learning, deployment, and scalable AI infrastructure for Kodiak's fleet.

Design, build, and operate ML infrastructure powering data, compute, artifacts, and orchestration across cloud and on-prem. Own backend services, storage, observability, security, and developer tools; collaborate with cloud/compute providers and lead reliability and scaling efforts.

The Optical Engineer will assess and enhance optical capabilities, design new optical systems, and collaborate on instrumentation solutions while contributing to data analysis and open-source implementations.