Top Senior Machine Learning Jobs in Sacramento, CA

The Senior Machine Learning Engineer will build and own production ML systems, manage end-to-end workflow, debug issues, and mentor others.

Design and develop AI capabilities and scalable microservices. Collaborate to integrate AI models and ensure performance in cloud environments.

Seeking a Senior Machine Learning Engineer to design and implement ML systems, optimize deployment, and collaborate with data teams, focusing on scalability and performance.

The Director of Data Engineering, ML & AI leads data strategy and AI capabilities, managing a team to enhance data infrastructure, machine learning systems, and sustainability analytics while driving company-wide AI initiatives.

The Machine Learning Engineer will develop and maintain scalable ML systems, collaborate across teams, and innovate solutions for real-time applications to enhance customer experiences.

Design, build, and scale MLOps infrastructure and CI/CD/continuous training pipelines. Deploy and monitor ML models as microservices or batch jobs, manage cloud GPU/CPU resources with IaC, enable observability for model drift and latency, and collaborate with data scientists, engineers, and product teams to ensure reproducibility, compliance, and production reliability.

Design, implement, and scale web and data pipeline solutions focused on generative AI and LLMs. Improve AI/ML infrastructure for model development, training, deployment, and prompt engineering. Partner with product and stakeholders to prioritize applied AI use cases, ensure PHI security and regulatory compliance, mentor junior engineers, and contribute APIs and integrations to embed generative AI into healthcare applications.

Lead design, training, fine-tuning, evaluation, and production deployment of TTS/voice-generation models. Translate research into reliable, low-latency production systems, define ML best practices, and collaborate across research, engineering, and product to drive execution.

Lead development and optimization of the compiler stack for ML systems, collaborate across teams, integrate and deploy products, map ML operations to hardware, and drive compiler infrastructure innovation and performance debugging.

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.

Develop AI-powered solutions for personalized content and marketing. Collaborate with teams to optimize ML models and pipelines at scale, mentoring engineers and driving strategic growth initiatives.

Serve as the presales technical expert for ML capabilities: lead discovery, architect ML solutions, run demos/workshops/proofs-of-concept, coordinate cross-functional teams, and inform product direction based on customer feedback.

Develop end-to-end perception solutions for autonomous driving, leveraging deep learning and data-driven approaches to enhance system accuracy and efficiency.

The Senior ML Engineer will develop and deploy full-stack AI solutions, manage LLM integration, and collaborate closely with defense clients to enhance real-world applications in secure environments.

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

The role involves developing and deploying machine learning models for forecasting within the Camus platform, requiring collaboration and technical depth in ML.

The Senior Databricks AI/ML Engineer will design and deploy AI/ML solutions in the insurance sector, focusing on Databricks architecture, data pipelines, and MLOps workflows, while collaborating with various teams to operationalize models and optimize processes.

As a Senior Technical Recruiter for AI/ML, you'll manage full-cycle recruiting for senior AI roles, build talent pipelines, and partner with leadership to close top talent effectively.

The Senior AI/ML Engineer will develop AI systems for enterprise decision-making, focusing on LLMs and real-time data processing. Responsibilities include building detection systems, insight engines, evaluation frameworks, and collaborating with engineers to ensure robust AI product engineering.

As a Senior MLOps Engineer, you will manage production ML systems, define lifecycle strategies, optimize ML pipelines, and collaborate with cross-functional teams to enhance ML operations.

As a Senior Staff Machine Learning Engineer, you will lead the development and deployment of machine learning models, ensuring they drive business growth and meet performance requirements. You will collaborate with teams, manage data pipelines, and implement state-of-the-art solutions while continuously improving model performance.

As a Staff Machine Learning Engineer - AI Tech Lead, you will lead the design of AI systems for security operations, focusing on scalable architectures, AI safety, and mentoring. Responsibilities include overseeing technical evaluations, production workflows, LLM fine-tuning, and collaboration with teams to enhance AI capabilities.

Design and implement machine learning algorithms for robotic manipulation, focusing on RL and IL. Collaborate across disciplines to ensure integration and successful deployment.

The job involves building responsive web dashboards, advanced data visualizations, and analytics tools for unmanned aircraft systems, requiring a deep understanding of UI/UX design and data presentation.

Design, build, and operate production-grade ML systems for personalization, search, and recommendations. Own end-to-end pipelines from data ingestion and modeling to deployment, monitoring, and iteration, ensuring scalable, reliable, and observable services.