Machine Learning Jobs in Sunnyvale, CA

Owns end-to-end evaluation and validation processes for autonomous vehicle software and end-to-end machine learning stacks. Designs scalable metrics, ELT infrastructure, automated triage strategies, and KPI monitoring using simulation and on-road data. Performs root-cause and behavioral analysis, communicates data-driven recommendations, and connects continuous improvement efforts to product safety cases and compliance standards. Collaborates with AI/ML, simulation, systems engineering, and product teams.

Serves as a technical lead for customers using CoreWeave cloud infrastructure, with emphasis on Kubernetes in high-performance computing environments. Responsibilities include designing and deploying tailored solutions, leading proofs of concept, optimizing AI/ML workloads, conducting technical reviews, advising on product strategy, collaborating with engineering teams, and representing CoreWeave at industry events.

Designs and implements evaluation, validation, testing, and simulation frameworks for autonomous vehicle software and ML systems. The role analyzes simulation and on-road data, develops performance metrics and confidence measures, performs root-cause analysis, automates regression detection, and communicates evidence-based insights to technical stakeholders. It requires strong Python skills, systems-engineering experience, analytical problem solving, and cross-functional collaboration.

Leads the strategy and execution of AI model performance and on-vehicle inference for autonomous driving. Responsibilities include managing engineering leaders, setting performance budgets, optimizing models and GPU systems, establishing benchmarking and profiling practices, detecting regressions, building performance dashboards, and guiding cross-functional architecture and production decisions. The role also oversees hiring, coaching, staffing, KPIs, technical leadership development, and trade-offs across latency, memory, throughput, accuracy, power, and numerical parity.

Designs and operates large-scale Kubernetes, hybrid-cloud, and data-center infrastructure; builds SRE tooling, Infrastructure-as-Code, GitOps pipelines, observability, SLOs, and automated runbooks. Develops AI- and machine-learning-driven incident detection and auto-remediation to reduce toil and MTTR. Leads reliability, disaster recovery, cost optimization, on-call operations, and incident management across global teams while mentoring engineers and driving DevOps adoption.

Analyzes workforce and healthcare data to identify trends, build predictive and machine learning models, and deliver actionable recommendations. Uses Python, Alteryx, and Power BI for analytics, visualization, and reporting. The role supports workforce strategy, employee engagement, organizational effectiveness, talent management, and healthcare cost insights. Responsibilities also include client collaboration, relationship management, team guidance, and applying risk adjustment and medical economics concepts to inform strategic decisions.

Leads GM’s autonomous vehicle evaluation organization, defining strategy, roadmaps, methodologies, infrastructure, metrics, risk assessment, and release-gating approaches. Oversees evaluation of perception, prediction, and planning systems using statistical and machine learning methods, scalable data platforms, workflows, and AI techniques. Builds and manages engineering teams, drives architectural decisions, establishes KPIs, aligns cross-functional stakeholders, and translates system-level results into decisions for engineering and executive leadership.

Principal Software Engineer leading architecture and technical strategy for an in-vehicle AI assistant platform. The role spans Android Automotive client applications, cloud services, edge-cloud orchestration, conversational AI, gRPC, streaming interfaces, testing, telemetry, and distributed systems. Responsibilities include cross-functional architectural alignment, roadmap development, resolving complex reliability and privacy trade-offs, integrating AI frameworks, and mentoring senior engineering teams.

Design and build AI-powered agent builder features and scalable fullstack web applications for the Moveworks Agentic Assistant ecosystem. Architect web technologies including authentication, event tracking, application platforms, design systems, and backend APIs. Collaborate with product, machine learning, and engineering teams to improve user experience and customer adoption while developing modular, reliable applications.

Design and implement intelligent automation for AV software development, testing, release, and operational workflows. Build CI/CD pipelines integrating simulation and hardware-in-loop testing, develop engineering data pipelines and metrics, and create AI-enabled tools for test analysis, failure classification, defect triage, reporting, and workflow orchestration. Establish evaluation, governance, security, and monitoring standards for AI solutions while improving release readiness, software quality, engineering productivity, and cross-functional visibility.

Build and operate a security data platform connecting SIEM, identity, asset, threat intelligence, and knowledge graph systems. Design core APIs, distributed data pipelines, schemas, risk scoring, entity resolution, and coverage queries. Own architecture and platform workstreams from scoping through delivery, collaborate with detection and identity teams, review code, mentor engineers, and drive partner adoption. The role requires expert Python, deep Splunk expertise, cybersecurity experience, and senior-level project ownership.

Supports data and analytics consulting projects through research, data analysis, visualization, predictive analytics, and machine learning tasks. Uses Python, SQL Server Data Tools, Power BI, Tableau, and Alteryx to manipulate data, validate findings, develop visualizations, and generate actionable insights. Collaborates with experienced professionals while learning consulting methodologies, artificial intelligence applications, and data-driven solution development.

Leads internal audit and SOX engagements, manages client relationships, develops audit methodologies, evaluates financial statements and internal controls, conducts risk assessments, and oversees audit reporting. The role includes project ownership, budgeting, stakeholder management, team leadership, mentoring, process improvement, and use of AI and risk technology to enhance audit effectiveness and address compliance and governance risks.

Leads an engineering team building scalable ML data infrastructure, including data ingestion, processing, storage, access, pipelines, and analytical platforms. Defines architecture, evaluates technologies, improves performance and reliability, translates data requirements into technical solutions, and ensures governance, security, and regulatory compliance. Provides mentorship, strategic roadmap input, and cross-functional collaboration with ML engineers, data scientists, platform engineers, and product teams.

Develops search relevance solutions for an enterprise question-answering platform. Responsibilities include creating and optimizing ranking features, building frameworks for diversified ranking, enabling parallel ranking experiments, and developing metrics to evaluate search performance. The role applies information retrieval, machine learning, text processing, and natural language understanding to address lexical gaps, semantic understanding, and data sparsity while collaborating with product, UX, customer success, and engineering teams.

Lead the architecture and strategy of autonomous vehicle evaluation systems. Develop metrics, statistical and machine-learning methods, automated workflows, dashboards, and release-gating criteria to assess AV performance, identify regressions, and support safety decisions. Collaborate with autonomy, simulation, systems, safety, and data teams across the development lifecycle. Analyze large-scale time-series data, investigate anomalies, influence technical strategy, and provide system-level insights for validated autonomous driving deployment.

Lead development of AI-powered employee experiences on a web surface. Define product specifications, success metrics, roadmaps, and strategic bets; partner with ML, engineering, UX, data science, marketing, and customer teams; translate user feedback and ambiguous problems into scalable enterprise capabilities; and guide rollout strategies and feedback loops for products serving large user bases.

Own the roadmap and execution for W&B Models, an experiment-tracking platform for AI researchers. Improve experiment organization, training visualization, monitoring, evaluations, and large-scale analysis across web and mobile. Conduct user research, translate ML workflows into product decisions, collaborate with engineering and design, and use data and feedback to launch polished, high-performing experiences. The role requires deep familiarity with ML research, technical product management, data visualization, AI tools, and developer or researcher audiences.

Design, implement, and optimize large-scale autonomous vehicle simulation testing pipelines and shared libraries. Build automation for test creation, data collection/analysis, debugging, and monitoring. Integrate AI tools to automate test generation and analytics, lead technical roadmaps, perform code reviews, and mentor engineers to improve AV behavior validation and deployment.

The Staff Product Manager will lead the product vision and roadmap for AV capabilities, ensuring successful delivery and alignment across teams while applying analytical insights to measure progress and drive improvements.

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.

Design, build, and operate production-grade agentic AI systems for ServiceNow. Responsibilities include multi-agent orchestration, tool use, planning, memory, failure recovery, enterprise-grounded reasoning, RAG and search pipelines, safety guardrails, observability, model integration, evaluation frameworks, and cost and latency optimization. The role also provides technical leadership through architecture decisions, code reviews, and coaching.

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

Lead AI engineering teams to design, build, and deploy end-to-end AI solutions. Manage client relationships, plan and deliver projects, mentor staff, drive adoption of cloud-native microservices, CI/CD, vector databases and orchestration tools, and ensure high standards of quality, innovation, and compliance.

Maintains internal technical education content and coordinates recurring Lunch and Learns, engineering demos, and training sessions. Responsibilities include speaker scheduling, notes and recording publication, content audits, editorial updates, research, drafting, request tracking, and improving content discoverability. The role partners with engineers and subject matter experts to turn technical material into accessible learning resources and supports instructional design and curriculum development.