Machine Learning Jobs in Fremont, CA

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.

Annotate robot episodes, videos, images, and sensor data for robotics AI models. Label objects, actions, task steps, and outcomes; write behavioral descriptions; identify ambiguous cases; perform annotation quality checks; meet accuracy and throughput goals; and report tool or workflow issues to engineering. The role requires high attention to detail, strong written communication, sound judgment, and comfort working under deadlines and ambiguity.

Lead the design and deployment of large-scale bioinformatics and omics pipelines spanning genomics, transcriptomics, and proteomics. Integrate multimodal biological data with machine learning, develop reproducible analysis frameworks, benchmark predictive models, and collaborate with wet-lab scientists to guide molecular engineering and experimental campaigns. Contribute novel computational biology algorithms, research roadmaps, and scientific leadership.

Supports payer modernization and health services consulting engagements by analyzing operational challenges, optimizing processes, applying business analytics, engaging stakeholders, implementing quality standards, and guiding transformation initiatives. Develops operational support frameworks, conducts market research, manages change, and advises clients on improving service delivery and business performance while mentoring junior team members.

Drive data-informed business decisions across carrier growth, product development, user acquisition, and partnerships. Lead A/B experiments, analyze customer and business performance, identify scalable growth opportunities, and automate manual processes to improve operational efficiency. The role partners with marketing, product, and business development teams and requires strong quantitative analysis, SQL, structured problem-solving, and communication skills.

Drive data-informed decisions across growth, product, marketing, and partnerships. Lead A/B experiment design and analysis, identify scalable acquisition and partnership levers, apply machine learning models to extract insights, and automate manual processes to improve operational efficiency. The role partners with cross-functional teams and communicates findings from frontline employees to executive leadership.

The Business Operations Associate will drive data-informed decisions across acquisition, partnerships, and product initiatives. Responsibilities include analyzing customer and business performance, designing and evaluating A/B experiments, identifying growth and profitability levers, and automating manual processes to improve operational efficiency. The role partners with marketing, product, and business development teams and communicates insights to audiences ranging from frontline employees to executives.

Lead data-driven analysis and business operations initiatives across marketing, product, and business development. Design and evaluate A/B experiments, identify acquisition and partnership growth levers, generate customer and performance insights, and automate manual processes. The role requires strong quantitative problem-solving, advanced SQL and data analysis skills, and the ability to communicate recommendations effectively from frontline teams to executives.

Build and deploy LLM-powered features for clinical, patient, and operational workflows. Responsibilities include prompt design, retrieval, tool use, agent orchestration, evaluation harnesses, feedback loops, production operations, and AI engineering tooling. Partner with clinical, product, and safety stakeholders to ensure responsible healthcare-grade AI. Mentor teammates, communicate model behavior clearly, and stay current with emerging AI research and development practices.

Leads global supply chain optimization by designing scalable processes, standards, training, metrics, and technology capabilities. Oversees procurement and ERP roadmaps, Oracle Fusion governance, AI and analytics adoption, MRP policies, standard costs, supplier performance, and continuous improvement. Drives transformation initiatives, change management, shared services, executive reporting, and M&A integration across divisions and geographies.

Design scalable human-data solutions for frontier AI clients, translating ambiguous model-training and evaluation needs into executable programs. Lead discovery, methodology, task and workflow design, feasibility estimates, expert profiling, quality strategies, and technical architecture in partnership with engineering and project teams. Advise on fine-tuning, RLHF, benchmarks, red teaming, multimodal data, coding tasks, and agent environments while guiding pilots through early delivery and developing reusable best practices.

Owns the strategy and roadmap for semantic insurance data products supporting AI, analytics, automation, and enterprise applications. Defines canonical concepts, relationships, metadata, data quality standards, APIs, knowledge graphs, and AI-ready consumption patterns. Partners with engineering, architecture, data, AI, UX, customer success, and insurance stakeholders to translate complex P&C insurance needs into product capabilities, prioritize use cases, establish requirements, drive adoption, and measure business impact.

Leads lab-in-the-loop biology programs that connect experimental design with machine learning model development. Oversees closed-loop experiments, model-output verification, perturbation studies, data generation, assay and model-system development, automation, metadata standards, CRO and vendor relationships, budgets, and cross-functional collaboration. Builds and mentors technical teams while aligning experimental and computational groups across a matrixed biotech organization.

Designs benchmarks, reinforcement learning environments, evaluation methodologies, scoring frameworks, and reproducible evaluation architectures for frontier models. Builds and ships production code, maintains data pipelines, analyzes results, and collaborates with research scientists, solutions architects, and ML engineers. The role combines independent research methodology with hands-on engineering across agentic systems, model evaluation, and RL infrastructure.

Develops and sustains semiconductor Advanced Process Control systems, including R2R control and FDC models, to improve wafer manufacturing yield, capability, cycle time, and equipment productivity. Leads APC automation projects, integrates machine learning and predictive maintenance capabilities, configures control strategies, conducts system testing, monitors performance, troubleshoots failures, and collaborates with process, equipment, IT, and external engineering teams.

Leads product strategy, roadmap, evaluation, and production maturity for humanoid robot perception and learned capabilities. Translates customer workflows into measurable requirements for world understanding, object recognition, learned behaviors, and autonomy. Partners with robotics, machine learning, simulation, software, and engineering teams to define metrics, benchmarks, technical trade-offs, dependencies, and deployment readiness. Communicates product direction and shapes long-term robot intelligence strategy.

Design, engineer, and optimize protein-based biosensors that convert neuronal activity into imaging signals. Build and characterize protein variants using computational design, directed evolution, combinatorial libraries, mammalian expression systems, and high-throughput assays. Collaborate with machine learning, biochemical, structural biology, and computational teams to model sequence-function relationships, develop screening methods, understand biomolecular mechanisms, and advance constructs toward in vivo applications.

Lead strategic sales and account growth for FANUC’s AI, robotics, and emerging technology ecosystem. Build executive relationships with robotics startups, AI companies, investors, universities, and enterprise customers. Develop account plans, identify automation opportunities, coordinate facility audits and partners, conduct business reviews, and influence product strategy through market insights. The role requires capital equipment sales experience, robotics or automation industry knowledge, C-suite selling experience, understanding of Physical AI systems, customer-site visits, and a valid driver’s license.

Own new business and account growth across hyperscalers, neoclouds, enterprises, and frontier AI labs in the Americas. Manage complex technical sales cycles, layered OEM/ODM and channel routes, capacity commitments, design-ins, pipeline forecasting, contracts, and executive relationships. Translate semiconductor performance, power, and TCO advantages into commercial outcomes while partnering with product, engineering, marketing, legal, and finance. Build a qualified pipeline through an existing customer network and represent the company at industry events.

Lead development of scalable molecular dynamics pipelines, integrating physics-based models with machine learning frameworks to enhance molecular engineering and experimentations.

Develop software for semiconductor equipment control, robotics, motion hardware, computer vision, and machine learning systems. Responsibilities include requirements and design specifications, C#/C++ implementation, unit and system testing, software integration, documentation, customer support, and cross-functional collaboration. The role develops image-processing algorithms and machine-learning models for object detection, tracking, segmentation, and depth estimation, while supporting Linux, APIs, databases, and containerized applications.

Serve as the technical sales and customer-facing expert for an AI platform. Responsibilities include conducting product demonstrations, supporting proofs of concept, advising on architecture and development, planning professional services projects, tuning retrieval and agentic pipelines, responding to RFPs, supporting customer adoption, and communicating product feedback internally. The role requires strong AI, cloud, on-premise, application development, storytelling, and enterprise customer engagement experience.

Own the full product lifecycle for AI-native insurance agencies and loss prevention services, spanning customer experiences, internal tools, automation, and integrations. Rapidly prototype MVPs with AI-assisted tools, define success metrics, analyze quantitative and qualitative feedback, align cross-functional stakeholders, and ensure regulatory and data security compliance. The role reports to the CEO and requires autonomous product ownership in a fast-moving startup environment.

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 wafer fabrication, equipment, sensor, metrology, and manufacturing data using AI, machine learning, statistics, and data-mining techniques. Develops data pipelines, analytical tools, dashboards, deployed models, and monitoring methods for anomaly detection, yield prediction, excursion analysis, and root-cause investigation. Collaborates with engineering, manufacturing, MES, and AI/ML teams to translate results into actionable insights, support experiments, improve processes, and establish responsible AI and data-quality practices.