Machine Learning Jobs in Sunnyvale, CA

Develop and optimize real-time computer vision algorithms and ML models for an autonomous anti-drone turret. Integrate CV systems with embedded hardware and sensors, conduct testing and validation across environments, and help harden prototypes into military-grade systems and variants for different weapons and ranges.

Lead development and optimization of real-time computer vision and ML models for autonomous turret drone detection, tracking, and classification. Integrate algorithms with embedded hardware and sensors, conduct robust testing across environments, and harden prototypes to military-grade systems.

Conduct graduate-level research on cyber attack and defense, focusing on threat detection. Study adversary behavior, develop detection logic and research tooling, and convert research problems into working prototypes for a security platform. Collaborate with security researchers and engineers while applying expertise in malware, network traffic, vulnerability exploitation, threat hunting, reverse engineering, offensive security, machine learning, and penetration testing.

Supports clients in transforming finance functions through process improvement, operating model design, analytics, automation, ERP/EPM implementation, and emerging technologies. Collaborates with finance executives, project teams, and cross-functional stakeholders to define strategy, manage risks, document requirements, and deliver digital transformation initiatives. Advises clients on finance technology, data solutions, regulatory trends, and best practices across industries.

Leads architecture and development of machine learning and large language model systems powering AI features for a network digital twin platform. Oversees agentic AI, natural-language workflows, API integrations, roadmap planning, cross-functional engineering execution, production incident response, hiring, mentoring, and performance management.

Annotate and manage training/test datasets, run model training, evaluate model performance, perform manual QA and error analysis, and refine annotation guidelines for NLP/ML projects.

Analyzes business and data requirements, converts them into machine learning and generative AI problems, integrates data from multiple sources, builds data models and dashboards, performs statistical analysis, develops predictive and AI models, and benchmarks model improvements. The role requires Python expertise, knowledge of data science and visualization tools, generative AI technologies, and relational and non-relational databases.

Leads the design, development, and deployment of scalable, reliable software and infrastructure solutions. Builds AI agents, automation workflows, observability integrations, and monitoring systems using technologies including C++, Python, Java, Claude, Codex, BigPanda, ITMP, and Prometheus. Collaborates across teams, drives engineering standards, mentors junior engineers, and manages complex end-to-end projects.

Lead and translate AI research into developer products: build datasets from public and internal code, design and run large-scale ML experiments, train state-of-the-art models, collaborate with product teams across Microsoft and GitHub, and evaluate and iterate AI systems for software engineering.

Lead cross-functional analytics for MSN & Copilot Discover to drive engagement and revenue. Build forecasting, scenario-planning, and ML solutions, evaluate UX/monetization tradeoffs, inform product and monetization strategy, and communicate insights to senior stakeholders to influence investments and business outcomes.

Build and operate full‑stack labeling tools and pipelines for autonomous vehicle ML. Design scalable UIs and services, integrate ML-driven annotation, create automation and QA tooling, own projects end‑to‑end, and collaborate with ML, Ops, Product, and Data teams to improve labeling quality and velocity.

Design, build, and operate scalable hybrid human/machine data-labeling tools and pipelines for autonomous vehicle ML. Implement full‑stack features (frontend, backend, APIs), integrate ML-driven annotation and active learning, build automation and QA tooling, and own projects end-to-end while collaborating with ML, product, and operations teams to improve labeling velocity and quality.

Leads strategy, architecture, delivery, and support for enterprise business intelligence, big data, and AI/ML solutions. Manages complex cross-functional projects, budgets, testing, governance, service levels, system performance, upgrades, audits, and incident resolution. Oversees contingent workers and coordinates technology teams, vendors, and business stakeholders to deliver reliable analytics platforms and services.

Build and operate production machine learning systems for ranking, retrieval, recommendations, search, propensity, churn, LTV, and next-best-action decisioning. Design reliable signal contracts covering freshness, provenance, confidence, eligibility, and calibration. Lead feature pipelines, model serving, experimentation, monitoring, and feedback loops while evaluating fairness, risk, compliance, trust, and long-term customer impact. Collaborate across product, growth, data, platform, modeling, risk, and compliance teams.

Build and operate production machine learning systems for ranking, retrieval, recommendations, search, propensity, churn, lifecycle intelligence, and next-best-action decisioning. Design reliable signal contracts with freshness, provenance, confidence, and calibration guarantees. Lead experimentation, monitoring, feedback loops, and impact evaluation focused on fairness, trust, risk, compliance, and long-term engagement. Partner across product, growth, data, platform, modeling, risk, and compliance teams.

Design, build, optimize, and scale machine learning infrastructure for training, evaluating, deploying, and serving large language models. Develop reusable workflow automation abstractions, distributed training and inference pipelines, model evaluation and monitoring frameworks, and latency optimizations. Collaborate with machine learning, data infrastructure, analytics, engineering, and product teams while establishing best practices for ML and data engineering.

Designs and delivers multi-modal technical learning programs for Sunnyvale engineering teams. Leads needs analysis, partners with senior technical stakeholders, facilitates training, owns program evaluation, and shapes technical development practice across sites.

The Director of Developer Relations leads the strategy for engaging developers around CoreWeave's AI SaaS offerings, creating content, fostering community, and improving the onboarding experience.

The Senior Director of Engineering leads engineering strategy, mentors teams, oversees project delivery, collaborates with stakeholders, and champions best practices for operational excellence.

Lead product strategy and roadmap for threat detection content across endpoint, cloud, and related domains. Partner with research, data science, engineering, marketing, sales, and support to deliver detections, competitive analysis, go-to-market plans, and AI-enhanced defenses. Drive cross-functional collaboration to prioritize features, influence product direction, and support customers and releases.

Designs and implements data warehousing, analytics, dashboards, semantic layers, and reporting solutions for supply chain planning operations. Collaborates with business, supply chain, and IT stakeholders to define requirements, document workflows, develop user stories, validate data, and improve SAP data accessibility through Databricks. Maintains data definitions and governance, tests data assets, ensures reporting accuracy, and supports self-service analytics. Requires deep supply chain experience, BI development expertise, and strong SQL, Python, and data modeling skills.

Own product development across e-commerce, education, operations, and wholesale. Responsibilities include identifying opportunities through analytics and research, managing requirements and launches, coordinating cross-functional projects, streamlining workflows, diagnosing bugs, and running A/B tests to improve conversion. The role also involves prioritizing initiatives, analyzing customer feedback and technical data, translating system architecture into requirements, and optimizing internal and consumer-facing products.

Own product development across e-commerce, education, operations, and wholesale. Identify and prioritize opportunities using analytics, research, and customer feedback; define requirements; collaborate with engineering, design, and business teams; manage launches and testing; streamline workflows; diagnose product issues; and conduct A/B tests to improve conversion and operational efficiency.

Leads the design, implementation, optimization, and support of SAP IBP and SAP APO supply chain planning solutions. Builds S&OP, demand planning, response and supply, network optimization, and constrained supply models. Applies AI, machine learning, statistical forecasting, demand sensing, anomaly detection, and LLM capabilities to improve planning. Partners with business and IT teams on requirements, integrations, testing, training, prototypes, and production solutions.

Define technical vision and architecture for agentic, multi-agent systems that improve autonomous-driving event triage and evaluation. Lead development of scalable frameworks supporting dynamic reasoning, planning, tool use, self-reflection, and orchestration. Identify applications across the Waymo Driver evaluation lifecycle, establish roadmaps, collaborate across teams, and mentor engineers. The role requires extensive software engineering and AI/ML expertise, technical leadership, and experience building complex production systems.