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.

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.

The Data Scientist will analyze and model data related to ad-tier members, focusing on identity modeling and improving ad targeting capabilities, while collaborating with cross-functional teams.

The role involves leading strategic AI partnerships, driving revenue growth, and managing cross-functional teams while advocating for AI initiatives internally and externally.

The Manager, Growth Analytics & Marketing Science will build and evolve marketing measurement frameworks, drive analytics, and optimize marketing strategies through data and AI.

The Core Engineer will develop backend systems, utilize AI tools for code quality, and optimize application performance while collaborating closely with teams.

The Senior Product Manager will lead the pricing and valuation engine, overseeing ML modeling, pricing systems, and improving valuation accuracy while managing cross-functional roadmaps and execution.

Co-found and lead a stealth startup building an agentic AI platform embedded in CAD tools to automate geometry updates, feature-tree edits, and cross-tool workflows. Drive product, engineering, and commercial strategy, hire the founding team, and develop a defensible data capture and automation stack for industrial CAD workflows.

This role leads the ML Acceleration team, focusing on enhancing ML model training efficiency and team management, while driving technical strategy and collaboration.

The Data Scientist will develop predictive models, analyze geophysical data, and collaborate with geoscientists to enhance exploration programs, focusing on mineral deposits.

Lead RWE study design and execution: develop protocols, statistical analysis plans, and R/SQL programs to produce analysis-ready datasets, tables, and figures; apply causal inference, time-to-event, and predictive methods; collaborate with scientists and stakeholders to deliver RWE insights.

The Principal Applied Scientist will lead the development of advanced computer vision and ML systems, optimizing solutions for real-time performance on edge devices and ensuring reliability in dynamic environments.

Lead and govern a multi-company consortium to drive digital transformation in supplier auditing using AI, automation, and blockchain. Oversee development of data dashboards and intelligence platforms, align stakeholders, translate insights into strategy, ensure regulatory readiness, and deliver measurable commercial and strategic value.