Machine Learning Jobs in Santa Clara, CA

Fine-tune and optimize LLMs (including multi-modal) for humanoid robots and autonomous vehicles; build scalable training and deployment pipelines; work on model efficiency (quantization, weight sharing), synthetic data generation, and cross-team product alignment.

Develop and maintain machine learning models for robotics applications, collaborate across teams, and contribute to innovative solutions in AI and mobility.

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

Seeking a Machine Learning Engineer to build models from idea to delivery, maintain production models, and develop system architecture while collaborating on data-driven strategies.

Design and implement machine learning models, optimize algorithms, deploy solutions, and collaborate with teams to enhance services through AI/ML solutions.

Lead the design, development, and implementation of machine learning models to solve complex problems, collaborating with cross-functional teams to enhance services and deploy solutions in production environments.

The job involves developing and optimizing machine learning models, overseeing model risk, and collaborating with teams on AI-related projects.

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

Lead the development of RL training frameworks and data processing pipelines for AV models, ensuring quality and scaling training workflows.

The Staff Machine Learning R&D Engineer will innovate machine learning algorithms for spatial computing, collaborate with teams, and translate research into production solutions.

Architect, build, and scale high-performance ML platform infrastructure using IaC (Ansible, Terraform). Apply SRE practices to ensure reliability across multi-cloud and on-prem GPU clusters, develop automation and orchestration tooling, operate Kubernetes/Docker workloads, participate in on-call rotation, and collaborate with researchers to support end-to-end ML workflows.

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

The Principal Engineer for AI/ML at McAfee leads the design and deployment of scalable AI solutions, mentors engineers, and drives technical strategies in a hybrid work environment.

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

Responsible for designing and optimizing VLSI circuits, translating requirements into data science problems, and building machine learning solutions. Collaborate on hardware design and integrate models into existing tools.

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

Develop and apply deep learning and data analysis techniques to create scalable vehicle simulation models, collaborating with teams to advance autonomous technology.

As a Staff Machine Learning Engineer, you'll build production-scale ML models for personalization and risk management, mentor junior scientists, and collaborate with cross-functional teams to drive impactful product features.

The role involves directing business outcomes, developing engineering strategy, driving product and technical strategy, and establishing organizational goals with cross-functional collaboration.

The intern will support the data science team by gathering data, performing exploratory analysis, building machine learning models, and developing visualizations to aid business insights.

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

Responsible for architecting high-performance machine learning silicon, collaborating with software and design engineers, and driving innovation in AI hardware solutions.

Design and implement distributed cloud GPU training for ML, build end-to-end pipelines, collaborate on data problems, and uphold ML best practices.

The Senior Machine Learning Engineer will design and build distributed systems for personalized content recommendations, ensuring deployment and optimization of ML platforms.