Machine Learning Jobs in Fremont, CA

As a founding Data Scientist/Machine Learning Engineer, you'll develop AI/ML models, enhance product capability, and drive impactful user outcomes while working closely with product teams.

The Principal Risk Quality Engineer leads the Risk Management process for AI/ML medical technology, ensuring safety, compliance, and risk assessment throughout the product lifecycle.

Design and deploy machine learning systems for autonomous vehicles, collaborating with teams to improve model performance and safety using real-world data.

Manage technical programs for generative AI video models, translating research into milestones, coordinating teams, and ensuring successful execution across all phases.

Recruit senior technical roles in Data Infrastructure and Machine Learning Engineering, collaborating with hiring managers and sourcing candidates from diverse platforms.

The role involves developing ML systems for enterprise workflows, focusing on user understanding, task prediction, and optimizing ML pipelines. Key responsibilities include designing scalable evaluation frameworks and collaborating with teams to deliver production-ready solutions.

Seeking a Research Scientist to develop AI models for enhancing 3D reconstruction processes, requiring strong skills in computer vision and neural reconstructions.

Own end-to-end labeling operations for AI/ML projects, manage labelers, design workflows, ensure quality, and drive process improvements.

The Lead Product Manager, AI will identify and build AI-powered products, drive growth and customer experience, and collaborate with cross-functional teams.

Lead the product vision for innovative AI technologies, translating research into marketable products, and collaborating with cross-functional teams.

Develop and deploy ML-based perception algorithms for robotics, optimize pipelines, and collaborate across disciplines for integration.

The role involves designing and implementing machine learning systems for knowledge representation and temporal reasoning, focusing on organizational intelligence. Responsibilities include building LLM-powered pipelines, developing memory algorithms, and researching various ML techniques.

The ML Engineer will develop and enhance machine learning models for credit decisioning, drive technical innovation, and collaborate across teams to deliver impactful solutions for small businesses.

You will build a search and assistant product, improve personalization, train models, and write robust code while mentoring junior engineers.

The role involves solving customer problems by building ML solutions, engaging with various stakeholders, and taking ownership of the outcome through deployment.

The MLOps Contractor will enhance data pipelines, develop and validate AI/ML models for semiconductor laser production, and collaborate with researchers and engineers for optimization and integration of ML approaches.

The role involves building production ML models for voice AI, focusing on fine-tuning, deploying, and evaluating models to enhance human-like interactions.

As a Machine Learning Engineer, develop ML models, data pipelines, conduct analytics, and work on image and video inference for fish health and behavior.

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

Design and build agentic AI workflows for biological and clinical data curation and analysis. Implement context engineering (RAG variants), prompt and agent architecture optimization, LLM tool-use integrations, and evaluation benchmarks. Collaborate with bioinformatics and clinical experts to translate domain problems into reliable, production-quality agentic systems.

The AI/ML Engineer will design and deploy advanced AI models, optimize performance, and directly engage with government officials to transform industries through innovative AI solutions.

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

The Machine Learning Engineer will design and implement advanced ML models for energy systems, collaborating with R&D teams to tackle challenges in battery technology.

This internship involves developing machine learning approaches for biological data, designing experiments, collaborating on research, and presenting findings.

Responsible for designing experiments to evaluate AI models, developing evaluation methodologies, analyzing performance data, and collaborating on production insights.