Machine Learning Jobs in San Jose, CA

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.

Conduct AI research for semiconductor manufacturing equipment, develop and evaluate solutions, translate research ideas into Python or C/C++ code, contribute to existing and new codebases, and share technical insights with the AI research team. Interns will complete meaningful project work, apply Lean principles, collaborate across cultures, and support the organization’s AI/ML research roadmap.

Process engineering intern supporting thin-film development in a research laboratory. Responsibilities include designing process optimization experiments, analyzing tool and metrology data, integrating plasma diagnostic signals, developing and validating reduced-order chamber models, simulating electromagnetic fields and plasmas, and performing supervised laboratory sample preparation and data collection. The role emphasizes Lean principles, continuous improvement, collaboration, and applying statistical, computational, and machine learning methods.

Own the strategy, roadmap, success metrics, and delivery of Splunk AppDynamics observability capabilities. Partner with customers, engineering, design, sales, marketing, and program teams to identify needs, prioritize requirements, launch scalable products, and drive adoption. Advance integrations across Splunk and Cisco platforms while supporting positioning, enablement, customer briefings, and competitive analysis across observability, AIOps, OpenTelemetry, generative AI, and application performance monitoring.

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.

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.

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.

Consultative Sales Engineer responsible for driving complex sales opportunities, designing cloud data security and data risk management solutions, delivering proof-of-value engagements and technical demonstrations, advising executive stakeholders, supporting partner channels, and coordinating cross-functional resources. The role requires cloud security, IAM, networking, databases, encryption, privacy, data governance, and strong technical communication skills.

Design and lead production agentic AI systems for CPQ workflows, including multi-agent orchestration, async execution, streaming, state management, tool boundaries, MCP and A2A interoperability, RAG, and context engineering. Own the agent execution Harness, make architecture and performance decisions, support classical ML pipelines, and provide full-stack integration across Python, Java/Spring Boot, React, TypeScript, and Lit. Work directly with customers and product teams to deploy solutions and set technical direction.

Own Samsung’s OPC modeling products by defining product specifications, descriptions, qualification criteria, and feature goals. Partner with R&D and headquarters product engineers on new development, technical requirements, support, acceptance testing, best practices, user guidance, and manuals. The role requires semiconductor and lithography expertise, programming and debugging skills, and daily onsite work in San Jose.

Build and lead NVIDIA’s enterprise data governance platform, covering sensitive-information detection, governed access, export-control enforcement, audit logging, data connectors, and AI knowledge readiness. Design scalable backend, distributed, and data-processing systems; integrate enterprise content sources; evaluate ML classification models; enforce access-control fidelity; and ensure ingestion quality. Provide technical leadership through architecture decisions, code and design reviews, mentorship, and cross-functional alignment with Security, Legal, Finance, and platform teams.

Research and develop machine learning and deep learning approaches for electronic design automation and system design. Design, implement, verify, and maintain software using C/C++, Python, Linux, and ML frameworks. Collaborate with worldwide cross-functional teams, develop APIs, and apply advanced ML techniques to VLSI CAD problems.

Designs customer-centered digital experiences, functional prototypes, user flows, wireframes, journey maps, and interface specifications. Collaborates with product, engineering, business, and research teams to define, test, and deliver solutions across responsive web and mobile platforms. Applies human-centered design, user research, usability testing, AI-assisted workflows, and responsible AI interaction patterns while facilitating workshops and supporting product prioritization.

Creates technically accurate marketing content and demonstrations, translates complex product concepts into customer-focused messaging, and supports launches, campaigns, webinars, events, developer outreach, partner programs, and sales enablement. Tracks content performance and audience feedback, maintains project and launch assets, presents to technical and business audiences, and collaborates with engineering, product, public relations, creative, and marketing teams.

Develop test software and automation for electrical testing of laser diodes and VCSELs. Build signal waveform preprocessing, analysis, and post-processing solutions for high-speed communications, including PAM4 metrics. Apply image processing and machine learning to testing methodologies, interface with hardware, and collaborate with engineering teams to deploy manufacturing test solutions. Maintain proprietary test-suite software using C/C++, .NET languages, Python, and related technologies.

Research, develop, and productionize motion-planning algorithms for autonomous trucks. The role covers decision-making, trajectory generation, optimal control, uncertainty-aware planning, and integration with perception, prediction, controls, and safety systems. Engineers use C++ optimization frameworks and robotics tooling to build safe, comfortable, reliable behavior for complex driving scenarios. Responsibilities also include system diagnostics, algorithm tuning, technical design reviews, and cross-functional collaboration in safety-critical environments.

Lead NVIDIA’s AI for Quantum product strategy, roadmap, and go-to-market initiatives. Translate AI and quantum research into scalable platforms, developer tools, APIs, libraries, and workflows. Partner with researchers, engineers, quantum hardware companies, institutions, and developers to identify applications across quantum design, control, calibration, error correction, and algorithms. Evangelize the platform through technical communications, identify new AI, HPC, and quantum opportunities, and present product strategy to executives.

Lead the technical direction for Zoom’s AI-powered virtual agent quality and reliability. Diagnose failures across models, prompts, and architecture; optimize prompts and prompt chains; build evaluation pipelines; and architect scalable production LLM systems. Collaborate across product, model, and engineering teams, mentor engineers, influence the roadmap, and drive measurable improvements in agent accuracy, resolution rates, and customer outcomes.

Leads global digital quality and intelligence strategy across quality and regulatory affairs. Oversees analytics, automation, AI, eQMS support, QMS modernization, governance, validation, roadmap execution, and inspection readiness. Directs global data, analytics, and software teams; manages portfolios, resources, risks, executive reporting, adoption, and change leadership. Ensures responsible AI, data governance, model oversight, and compliant deployment within regulated life sciences environments.

Updates machine learning training and test datasets, refines annotation guidelines, initiates model training, and evaluates model performance. The role annotates synthetic text and image data, conducts manual quality analysis, identifies error patterns, reports anomalies, and produces findings on utterance quality, LLM evaluation, ASR bugs, and customer pain points. It also applies basic NLP and linguistic knowledge to ensure data accuracy and consistency.

Conduct applied computer vision and deep learning research for automated construction drawing takeoff and estimation. Own a scoped research problem, train and evaluate models for detection, segmentation, or structured extraction, explore self-supervised learning and multimodal signals, develop prototypes using real data, design evaluations, and present findings to the research team.

Build and calibrate an agent evaluation platform for multi-step LLM agent trajectories. Design rubrics, deterministic validators, LLM judges, confidence scoring, and human calibration workflows. Fine-tune judge models, analyze simulation-versus-production divergence, and develop process reward models for agent optimization. Establish versioned scenarios, simulated environments, and reliable measurement standards while maintaining production-grade Python code.