Top Senior Machine Learning Jobs in Sacramento, CA

The Solutions Engineer will drive the adoption of AI-powered solutions in the electric utility sector, providing technical consulting and customer enablement. Responsibilities include gathering requirements, architecting solutions, leading RFI/RFP processes, and delivering training. Extensive travel is required for client engagement.

As an AI/ML Ops Engineer, you will architect and operate ML pipelines, automate CI/CD processes, and collaborate with cross-functional teams to enhance engineering productivity.

Lead development of a large-scale machine learning platform, optimizing model training, data processing, and collaborating on MLOps, while ensuring scalability and performance.

The Machine Learning Engineer will enhance search retrieval, train ranking models, build query understanding systems, and ensure robust pipelines for Reddit's AI-driven products.

The Senior Full Stack Engineer will develop AI/ML features for ClickHouse Cloud, integrating AI capabilities and building user-friendly interfaces.

As a ML Engineer focused on inference, you'll design and optimize deep learning models for real-time communication AI applications, collaborating with cross-functional teams and ensuring production readiness.

Lead AI and machine learning projects, create workflows and models, analyze data from diverse sources, and present insights to non-technical audiences.

Design and maintain scalable machine learning infrastructure, collaborating with data scientists, ensuring performance, security, and compliance of AI systems.

The Staff Software Engineer, AI/ML Focus will lead AI product development, ensure system reliability and security, and collaborate with cross-functional teams to innovate tools and products.

Join DICK'S Sporting Goods as a Senior Machine Learning Engineer, focusing on AI-driven search solutions that enhance decision-making and engagement across the organization.

The Engineering Manager - Data & ML will redesign and scale Underdog's data and ML platform, establishing best practices, leading a team, and collaborating with cross-functional teams to optimize data systems.

As a Senior ML Ops Engineer, you'll build ML infrastructure, implement automated deployment, optimize model serving, and ensure production performance.

The Senior Product Manager will lead the strategy and execution of AI-driven features in a SaaS platform, ensuring high-quality user experiences and data-driven decisions while mentoring junior team members.

Lead the development of AI agents and infrastructure, collaborate with stakeholders, design APIs and SDKs, and advocate for best practices.

Design and deploy machine learning models for autonomous vehicles, focusing on data tagging, dataset curation, and model validation.

As a Sales Executive, you will hunt for new clients, manage enterprise accounts, and create revenue streams while collaborating with internal teams.

The Solutions Architect for AI/ML at Snowflake will advise clients on best practices for Data Science workloads, design solutions, and build ML pipelines. Responsibilities also include working hands-on with SQL and Python, maintaining technical expertise and collaborating with teams to improve products.

As a Senior Machine Learning Engineer, you'll design and implement ML models, develop data pipelines, and collaborate on AI features at Mural.

The role involves developing AI-driven features for observability tools, collaborating with cross-functional teams, and delivering scalable solutions.

The Machine Learning Engineer will fine-tune and deploy Large Language Models, optimize ML models, maintain data pipelines, and collaborate on AI features.

Develop and optimize machine learning models for financial and operational workflows at Netflix, ensuring model reliability and integration with studio applications.

The role focuses on enhancing detection frameworks using machine learning to identify malicious activities and minimize risks for Netflix.

Build and deploy ML systems that detect fraud and automate security decisions, while collaborating with cross-functional teams.

The Staff AI/ML Engineer will lead AI product development, ensure system health, and collaborate with teams on product features while maintaining security and compliance.

The ML Platform Engineer will develop and scale ML infrastructure, automate workflows, and collaborate with data scientists to deploy models efficiently in production.