Top Remote Machine Learning Jobs in Sacramento, CA

The Machine Learning Engineer will design, build, and maintain production machine learning systems, focusing on scalability, reliability, and integration with existing products. Responsibilities include developing ML pipelines, establishing ML Ops best practices, and collaborating on product capabilities.

The Senior Applied AI/ML Scientist will lead the design and deployment of AI solutions, collaborate on impactful features, and enhance product capabilities by leveraging advanced AI and ML techniques.

The Machine Learning Engineer develops production ML algorithms and recommendation systems, collaborates with teams, and optimizes user experiences.

The Principal AI/ML Engineer will develop machine learning models for campaign optimization in AdTech, collaborating across engineering and product teams to enhance advertising capabilities.

The engineer will build and operate AI/ML infrastructure, managing services on AWS and bare metal, using tools like Kubernetes and Terraform.

Develop ML/RL models and infrastructure for AV simulations, optimize training loops, and support project timelines in autonomous vehicle tech.

As a Senior Staff Machine Learning Engineer at Affirm, you will lead complex ML system design and implementation, mentor engineers, and drive innovative ML strategies for financial services.

Lead the ML Data Enablement team to define strategy and execution for accelerating third-party and internal data onboarding, enforce data quality and SLAs, build metadata and lineage standards, and deliver scalable data infrastructure and workflows to reduce time-to-production for ML models.

As a Staff Machine Learning Engineer, you will design AI products on Edge devices, optimize ML model performance, and work with large-scale datasets, collaborating across teams to deliver impactful solutions.

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.

The Talent Researcher role involves building talent maps in AI, ML, and voice technology, translating hiring signals into research plans, and delivering market intelligence to enhance recruitment processes.

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 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.

The Generative AI Analyst will create prompts and responses for machine learning projects, lead labeling initiatives, and provide training on best practices for LLM datasets.

As a Data Scientist, you will build predictive models, develop software tools, and analyze geoscientific data to support mineral exploration and discovery.

As a Staff AI Engineer, you'll design and implement components of an AI tutoring system, conduct experiments, and create scalable systems integrating LLM capabilities, ensuring high-quality learning experiences.

As a Senior Machine Learning Engineer, you'll develop models for risk identification, collaborate cross-functionally, and deploy ML solutions, ensuring performance monitoring and continuous improvement.

As a Machine Learning Engineer, you will develop and operationalize models for content understanding and discovery, collaborating with cross-functional teams and stakeholders to solve impactful problems using machine learning.

Lead the Client Solutions team, ensuring the execution of complex transactions while driving innovation and client advocacy. Oversee operations, build client relationships, and implement strategic frameworks for growth.

Participants are needed for an AI technology research study, offering compensation up to $600 for ~1.5-2 hours of participation over one week, requiring skills in tech-related roles.

The Business Analyst 2 analyzes AI-powered data solutions, optimizes customer experience automation, and collaborates with teams to drive business insights and value.

The Director of Adversary Engineering will define strategies for log management and security automation, lead the development of automated workflows, and optimize security systems using AI/ML techniques.

As a Principal Data Scientist, you'll design and deploy cutting-edge machine learning models to drive financial success for customers and guide technical teams.