Data Science Jobs in Sunnyvale, CA

The Senior Product Manager for Evaluation Applications will define and implement strategies for a testing platform, ensuring cohesive workflows. This role requires strong technical leadership, stakeholder alignment, and a focus on data-driven insights for autonomous vehicle evaluation.

As a Staff Machine Learning Engineer, you will enhance credit modeling, manage full credit modeling stacks, and support innovations within regulated banking frameworks.

Lead product definition and roadmap for internal web tools that surface and audit autonomous vehicle log events. Partner with engineers, data scientists, safety, and operations to translate complex AV workflows into requirements, prioritize features, improve reviewer productivity, define success metrics, and deliver scalable, reliable visualization and triage tooling.

Define value propositions, positioning, messaging, and GTM for CoreWeave's AI researcher and developer tools. Drive product launches, sales enablement, customer advocacy, market insights, and metrics-driven measurement in close partnership with Product, Engineering, Sales, and Marketing teams.

The Group Product Manager for AV Capabilities at GM leads the strategy and roadmap for autonomy products, managing a team while collaborating cross-functionally to ensure quality delivery and innovation.

Lead a team of data scientists to enhance infrastructure through data science, focusing on capacity planning, performance optimization, and customer experience.

Join Hiring.Cafe as a Founding Machine Learning/AI Search Engineer to develop AI recommender systems and scalable infrastructure, contributing to a transformative job search engine.

The Principal Product Manager will lead strategic initiatives in Unity Ads, enhancing ad quality, privacy strategies, and trust efforts while collaborating with cross-functional teams to drive product vision and execution.

The Sr. Solution Engineer collaborates with Sales to advance enterprise opportunities, conducting demos, workshops, and assessments to align with customer needs and position Aera's Decision Intelligence platform as a transformative solution.

Install, qualify, maintain, and optimize photolithography equipment in a semiconductor fab. Drive yield, uptime, and process stability; troubleshoot and repair tools; partner with process engineers; manage vendors and tool metrics; write purchase requisitions; implement TPM; work in a cleanroom and follow EHS and ISO quality standards.

As an Automation Engineer, you'll build automation pipelines, collaborate on experimental needs, program instrumentation, and integrate with data science, enhancing research capabilities.

The Director of Data Science leads data-driven initiatives, focusing on strategy, technical execution, and cross-functional collaboration to drive business impact through advanced models and teamwork.

Lead AI strategy and initiatives for Samsung by creating growth roadmaps, identifying high-value use cases, and translating strategy into action, while fostering responsible AI practices and cross-functional collaboration.

The Principal Data Scientist will adapt complex statistical concepts for executive decision-making, lead communication standards within the data science organization, and represent Databricks at industry events. Responsibilities include mentoring, producing strategic insights, and advancing scientific methodologies.

Maintain and improve analytics solutions and financial/marketing models (primarily in Excel); perform ETL/data wrangling; analyze market and business data; communicate concise insights to stakeholders; drive data-informed strategic decisions and build production-ready data products or pipelines.

As a founding Data Scientist/Machine Learning Engineer, you'll develop AI/ML models, enhance product capability, and drive impactful user outcomes while working closely with product teams.

The Market Intelligence Manager will drive strategic analysis, support CEO initiatives, and deliver business insights by analyzing market data and trends.

The Engineering Leader will oversee software and data teams, ensuring product delivery and operational excellence in robotics and IoT systems.

Lead global product strategy and lifecycle for large-scale network orchestration, telemetry, and analytics products. Define technical use cases and architecture requirements, guide cross-functional teams, engage customers and partners, and deliver scalable datacenter networking solutions aligned with NVIDIAs AI infrastructure roadmap.

Lead a team to design, build, and deploy production-grade end-to-end AI systems (generative AI, agentic intelligence, recommendation, measurement/causal inference). Drive technical strategy, mentor data science and engineering teams, and align AI roadmap with product, UX, and business stakeholders to deliver supplier-facing insights at scale.

Lead data science strategy and a rapid-prototyping team to build production-grade ML and GenAI solutions for contractor earnings, tax, and compliance. Drive model governance, automation, and cross-functional delivery to reduce errors, mitigate risk, and scale measurable ROI across product, engineering, and operations.

Lead design and development of data engineering and AI/analytics solutions for Azure-scale platforms. Identify AI opportunities, build data pipelines, analytics, and visualizations, and collaborate with engineers, scientists, and program managers to deploy data-driven solutions improving cloud hardware quality and efficiency.

Lead and grow a Product Data Science team to drive modeling, experiments, and data analysis that improve Waymo Driver performance and operational efficiency. Partner with senior leadership and cross-functional teams to prioritize resources, support geographic expansion, and translate vehicle and operational data into scalable product decisions.

Lead and grow a data science team to analyze large power-grid datasets, define metrics and annotation strategies, design experiments (A/B tests), and deliver ML-ready production solutions that improve grid visibility, resilience, and product impact while aligning cross-functional stakeholders.

Design and build data models and pipelines to produce research-ready multi-modal surgical datasets. Drive data collection and quality frameworks, manage annotation workflows, partner with AI/ML researchers, build researcher tooling, and collaborate across clinical, robotics, and systems teams to support embodied AI research.