Machine Learning Jobs in Sunnyvale, CA

Design, deploy, and maintain end-to-end ML-driven risk solutions at scale to detect and prevent fraud, abuse, and credit risk. Lead technical decisions, build ML tooling and processes, apply state-of-the-art models and third-party data, investigate emerging risk patterns, and collaborate with platform and cross-functional teams to ensure reliable real-time model operation.

As an AI/ML Engineer, develop and optimize analytics frameworks to enhance autonomous vehicle development, focusing on automation tools and collaboration with engineering teams.

Lead the design and implementation of advanced ML models for autonomous driving, collaborating with teams, mentoring engineers, and driving technical initiatives.

This role involves driving AI strategy and infrastructure investments at Google DeepMind, overseeing high-stakes decisions that shape Google's AI product portfolio and future.

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 Technical Program Manager drives cross-functional project execution, manages schedules, identifies risks, and ensures alignment on technical goals for Waymo's autonomous systems.

Develop and productionize ML models for assessing autonomous vehicle behavior, build ML infrastructure, and collaborate across teams for deployment.

As a Senior Technical Recruiter, you will design and execute hiring strategies to attract software engineering talent, manage multiple searches, and mentor other recruiters.

Lead a team of engineers in developing offline perception algorithms and data mining tools to produce high-quality data for autonomous driving.

Lead technical vision and strategy for next-generation graphics developer tools. Design and prototype tooling, drive cross-team initiatives, mentor engineers, engage external developers and partners, and deliver production-ready solutions that improve graphics development, debugging, profiling, and optimization workflows.

Lead end-to-end supply planning strategy and governance for networking products (optics, switches, adapters). Build scalable planning frameworks across chips, memory, capacity, and manufacturing; ensure data integrity (BOMs, yields, cycle times); accelerate time-to-market via complexity reduction and AI-enabled planning; and manage and develop global supply planning teams.

The Curriculum Product Manager will collaborate with AI experts to create courses, ensure content quality, and enhance learning experiences in AI and machine learning.

Design and build a scalable failure-attribution framework for heterogeneous CPU/GPU clusters: collect high-fidelity telemetry, implement low-overhead tracing, automate root-cause classification (hardware, software, environment), and enable proactive resiliency measures like migration or checkpointing.

Lead and coordinate cross-functional engineering programs for deep learning software and GenAI model initiatives. Plan, forecast, track dependencies, report status, implement metrics, guide agile practices, moderate technical discussions, and drive organizational alignment to meet business objectives.

As a Senior Software Architect for AI Networking, you'll design and implement AI networking technologies, optimize data processing in AI systems, and collaborate on cutting-edge solutions.

Assist in developing software for autonomous driving vehicles, participating in project work involving machine learning, coding, and testing.

As a Sr. Software Engineer, you'll enhance Databricks' customer support with AI-driven systems, ensuring improved automation and user experience across support engineering operations.

Lead finance-focused AI and automation transformation: identify and prioritize high-value AI opportunities, run pilots and prototypes, define data and control requirements, and scale AI-enabled finance workflows while driving adoption, governance, and measurable value realization across Finance.

Lead process-integration projects to improve yield, device performance, and manufacturability. Design experiments, apply statistical and machine-learning analysis to large datasets, qualify new technologies for HVM, collaborate cross-functionally to identify root causes and implement corrective solutions, and support foundry customer requirements and NPI activities.

Lead supply planning strategy for Boards and Systems products, develop scalable planning frameworks across components, ensure data integrity (BOM, yields, cycle times), accelerate time-to-market using advanced/AI planning, and manage global supply planning teams.

Design, build, and operate production ML decision systems to detect and prevent payment fraud, account takeover, scams, and other abuse. Integrate diverse signals into low-latency serving and batch scoring, own feature pipelines and model lifecycle, develop AI-assisted triage and feedback loops, and partner cross-functionally to balance fraud reduction with legitimate customer access.

In this role, you will lead AI personalization initiatives, develop AI/ML models for user experience, collaborate across teams, and ensure rigorous development practices.

Design, build, and operate production ML systems that generate trusted signals for ranking, retrieval, recommendations, propensity/churn/LTV, and next-best-action decisioning. Define signal/data contracts, own feature and candidate generation through serving, experimentation, monitoring, and feedback loops, and evaluate long-term business impact, trust, fairness, and compliance. Partner across product, data, modeling, risk, and compliance and apply AI/agents to accelerate engineering and operations.

The VP of Product will lead CoreWeave's Research Training Stack, focusing on enhancing AI infrastructure, ensuring quality for pre-trained models, and connecting researchers with advanced cloud capabilities.

Build and scale a generative conversational AI platform: design APIs, optimize dialog engine for low-latency and low-memory multilingual enterprise usage, implement logging/tracing/metrics, create tooling and interfaces for customization, and collaborate with ML, product, and support teams to deliver robust, scalable solutions.