Top Machine Learning Jobs in Sacramento, CA

The role involves designing, training, and evaluating ML models, optimizing performance, and collaborating with teams to implement AI technologies in products.

The Machine Learning Systems Engineer will optimize ML training systems, improve data pipelines, and develop GPU kernels to enhance scalability and performance.

The AI/ML Engineering Manager leads a team of ML engineers and architects, managing hiring, performance, and customer engagements while providing technical guidance in ML operations and architecture.

Develop and deploy production-grade AI/ML models, design end-to-end pipelines, and ensure compliance while collaborating with stakeholders in a federal environment.

Lead a team of data scientists developing ML-driven products, managing infrastructure, training models, and ensuring production quality while collaborating with senior leadership.

Lead and grow the AI/ML Engineering team, manage core AI/ML platform development, ensure production-grade service operational excellence, and develop product strategies.

The Senior Manager, Data Science/ML will lead a team to enhance product innovation through data science, focusing on ML and experimentation frameworks that boost customer engagement. Responsibilities include defining product strategy, building ML models, and collaborating with cross-functional teams to shape product roadmaps.

As a Data Scientist/Machine Learning Engineer, you'll finetune models, improve data quality, add new signals, and push solutions to production.

As an Applied Machine Learning Platform Engineer, you'll design and maintain training infrastructure, manage distributed pipelines, and optimize data workflows for machine learning models.

Develop and deploy advanced ML solutions for OCR and NLP, optimizing models for performance and integrating them into production workflows while collaborating with cross-functional teams.

The Senior Machine Learning Engineer will design, train, and deploy ML models for optimizing revenue in advertising, taking ownership of product development and leading the ML discipline.

The Principal AI Platform Engineer will design and maintain the infrastructure for AI systems, ensuring integration, security, and scalability for GenAI products.

The Principal Machine Learning Engineer will fine-tune and optimize LLMs for various applications, develop AI products, and enhance ML infrastructure in collaboration with cross-functional teams.

As a Machine Learning Engineer, you will design and build AI capabilities, develop scalable ML infrastructure, and collaborate on production systems in the real estate domain.

As a Senior Machine Learning Engineer, you'll design and develop infrastructure and models for AI-powered applications while collaborating with teams to enhance product functionality.

The Lead Machine Learning Engineer will design and evaluate models for autonomous driving systems, mentor junior engineers, and utilize large datasets to improve ML capabilities at May Mobility.

The role involves applying AI/ML techniques to develop model systems for healthcare, collaborating across teams, and conducting R&D.

The role involves developing and optimizing machine learning systems for voice experiences, focusing on speech recognition and language understanding. Responsibilities include training models, ensuring performance metrics, and collaborating with cross-functional teams for successful deployment.

The VP of Research, Machine Learning will set research direction for AI systems, focusing on context representation, reasoning, and evaluation frameworks while ensuring product safety and alignment.

Responsible for building and maintaining end-to-end ML pipelines and deploying production-grade ML systems. Tasks include model fine-tuning, evaluation, and collaboration with engineering teams.

The MLOps Engineer will design and maintain the machine learning operations infrastructure, optimize cloud services, and build CI/CD pipelines to support AI products for underground infrastructure management.

Lead the development of device intelligence and fingerprinting systems by designing backend services, collaborating on integrations, and applying advanced machine learning algorithms to enhance security and combat fraud.

Develop, evaluate, and deploy AI systems and machine learning models, focusing on NLP and multimodal models. Collaborate with teams and publish research.

The Senior Machine Learning Operations Engineer will design, build, and maintain ML infrastructure, streamline model deployment, and monitor performance to ensure the success of machine learning models at The Athletic.

The Senior ML Engineer will automate component placement on PCBs, working on R&D and production using ML and optimization techniques.