Machine Learning Jobs in Oakland, CA

The Applied Scientist will transform raw data into actionable insights by developing machine learning models for personalization, ranking, and optimization to enhance conversion and revenue. This role emphasizes building production systems, frameworks for experimentation, and communication with team members regarding technical challenges.

Lead development and execution of a multi-year automation and AI/Industry 4.0 roadmap for manufacturing. Build and mentor a multidisciplinary automation team, oversee end-to-end program delivery (concept through commissioning), integrate ML/vision/IoT/SCADA systems, manage budget and metrics, and drive measurable improvements in safety, quality, throughput, and cost.

The Solutions Engineer will engage with stakeholders to design AI-powered engineering solutions, bridging business needs and technical execution while guiding customers through AI integration.

Lead FP&A strategy and transformation: provide senior leadership with insight-driven financial storytelling, scenario and long-range planning, advanced modeling, automation and AI-enabled analytics, cross-functional financial leadership, and build a high-performing FP&A team while ensuring governance and continuous improvement.

Support hydrogeology, water resources, hydraulics, and geotechnical projects through data collection, modeling, analysis, visualization, field work, and client communication; assist with proposals, project management, and business development under supervision.

Design, build, and operate production ML decision systems to detect and prevent payment fraud, account takeover, identity abuse, merchant/marketplace risk, scams, and other adversarial activity. Own end-to-end production lifecycle: data contracts, low-latency inference, batch scoring, feature quality, deployment, monitoring, incident response, rollback, and feedback loops. Develop AI-assisted workflows and reusable decision capabilities while partnering with modelers, product, compliance, and operations.

Design, build, and operate production ML signal systems—ranking, retrieval, recommendations, propensity, and next-best-action—covering feature/candidate generation, serving, experimentation, monitoring, and feedback. Define signal contracts (freshness, provenance, confidence), evaluate long-term impact (trust, fairness, compliance), and partner across product, data, and risk teams to deliver reusable customer-intelligence capabilities.

The role involves leading a research project on large language models, mentoring junior researchers, and publishing scientific papers, with a focus on advanced natural language processing methods.

Lead and grow a team of Technical Program Managers who run customer data projects end-to-end: staffing cadence, project setup, throughput and margin tracking, AR/billing hygiene, Airtable as system of record, onboarding TPMs, operational playbooks, and escalation for delivery risk. Serve as a player-coach partnering with Deployment Leads, FDE Manager, and GMs to ensure projects are staffed and delivered reliably.

The role involves designing and deploying strategies for congestion revenue rights, applying quantitative methods, and developing machine learning models.

Partner with portfolio and risk managers to develop quantitative risk models, analyze U.S. power markets, improve backtesting and simulation infrastructure, attribute performance, track P&L and exposures, and deliver actionable insights to scale the trading and risk platform.

Support development of pricing arrangements, financial models, budgets and AFAs for a law firm. Produce pricing analyses, competitive market research, and performance metrics. Collaborate with attorneys, IT, and data teams to implement pricing tools (Elite 3E, Iridium), leverage AI/analytics for forecasting, and train stakeholders on pricing technology.

Lead AI-centered product design strategy for Everlaw's litigation platform, define human-AI design frameworks, influence cross-functional product and engineering decisions, mentor designers, and elevate org-wide design systems and standards.

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.

The Sr. Director of Manufacturing Engineering leads manufacturing functions, optimizing processes and equipment while driving innovation, safety, and efficiency in high-precision production environments.

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

The Principal Product Manager will drive AI technology strategy and product vision for intelligent manufacturing systems, collaborating with AI teams to define capabilities and improve production efficiency.

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.

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.

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

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

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.

The ML Platform/MLOps Engineer will build and maintain infrastructure for large-scale ML systems, ensuring efficiency, reliability, and security while supporting the research team from experiments to production models.

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.