Top Machine Learning Jobs in Sacramento, CA

Lead the Machine Learning Engineering team at AKASA, focusing on improving ML capabilities, model deployment, and infrastructure development, while managing and mentoring engineers.

Design, build, and scale production ML systems (including LLMs) to automate customer support and compliance workflows. Lead technical roadmaps, write high-quality Python code, mentor engineers, ensure secure, scalable architectures, and resolve complex reliability issues.

Partner with CV researchers to productionize models, optimize training and real-time inference performance, design reusable abstractions, and collaborate with MLOps/backend teams to evolve the CV inference platform for scale and reliability.

Lead complex cross-functional technology projects, ensuring timely delivery through strategic planning, proactive risk management, and effective communication with stakeholders.

Drive execution of AI-driven threat detection and analytics: translate models, graph analytics, and data pipelines into shippable product features, define success metrics, coordinate integrations, prioritize initiatives, track risks, and support post-launch improvement.

Lead and scale Zapier's AI/ML organization by defining strategy, delivering ML products and platforms, coaching teams, enabling product partners, and ensuring safe, reliable, cost-effective model deployment and operations.

The Staff Machine Learning Engineer will design and build scalable ML systems, mentor engineers, and drive AI strategy at SailPoint, focusing on AI-powered identity security solutions.

The Senior Applied Scientist II is responsible for designing and implementing ML models to optimize the supply chain, collaborating across teams, and driving data-driven decision-making.

The Senior Machine Learning Engineer will develop ML APIs, build data pipelines, and collaborate across teams to enhance ML models and applications.

As a Senior Machine Learning Engineer, you will design ML infrastructure, lead zero-to-one initiatives, collaborate on projects, and enhance scalability in the development of ML applications.

The Senior Industry Marketing Manager will drive marketing strategy for AI/ML, develop initiatives, create content, and collaborate with sales teams.

The Director of AI will lead AI and machine learning initiatives, develop AI architecture for humanoid robots, oversee production-ready AI systems, and manage team growth and budget.

The Product Operations Associate will support the development of AI-driven products by ensuring accuracy, documentation, and effective workflows, while collaborating with various teams.

Own U.S. client relationships: act as main contact for strategic accounts, manage renewals and contracts, identify upsell/cross-sell opportunities, monitor client health, maintain CRM records, gather client feedback, and help grow long-term partnerships.

Lead the development of AI-powered tools and products, manage product roadmaps, collaborate cross-functionally, and drive innovation in media and advertising.

Partner with Account Executives to deliver technical demos, PoCs, and proposals; design integrations and architectures; support evaluations, onboarding, and cross-functional handoffs; train teams and build technical assets.

Lead the Intelligent Document Processing product to improve extraction and classification accuracy. Define the IDP roadmap, partner with Data Science and Engineering to raise F1/precision/recall, manage ML model lifecycles at scale, benchmark competitors, optimize human-in-the-loop workflows, and ensure extracted data integrity across enterprise systems.

As a P&C Actuary, you will assess risks for insurers, support audit teams, and maintain compliance with regulations, while growing client relationships and improving tools for efficiency.

Lead content programming through analysis, classification, and editorial judgment. Monitor performance, synthesize query analysis, propose product improvements, curate content, and collaborate with Engineering/Data Science on LLM/ML/NLP initiatives.

Lead Yahoo's Data Activation product area: define vision and strategy, partner with Data Science and Engineering, drive cross-vertical data activation initiatives, deliver measurable business impact, and mentor/manage product teams to execute on audience, personalization, and targeting use cases.

The Senior Data Scientist will design, develop, and own machine learning systems for document verification focusing on computer vision and deep learning. Responsibilities include technical leadership, engaging with customers, and collaborating with engineering and product teams.

The role involves managing a client portfolio of Chief Data Officers, delivering insights on data strategy and analytics, mentoring clients, and fostering collaboration with internal teams to ensure client satisfaction and retention.

Lead multi-team technical strategy and architecture for large-scale, long-lived systems. Design for scalability, reliability, and maintainability; integrate and productionize ML/NLP and anomaly detection; define testing and validation frameworks; align cross-functional teams and mentor engineers to deliver high-quality, business-driving solutions.

As a Senior Machine Learning Engineer, you'll build and deploy ML models for risk and fraud detection, leading technical efforts and collaborating cross-functionally.

Lead a team optimizing backend systems for Netflix's Member Experience Pages. Focus on performance, scalability, architecture, and team growth while collaborating with various stakeholders.