Machine Learning Jobs in Sunnyvale, CA

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

The Software Engineer will develop infrastructure for ML models, optimizing the economic engine for ride-hailing services and managing backend platforms for real-time decision-making in pricing and vehicle matching.

The role focuses on measuring and improving the quality of AI assistants through evaluation datasets, large-scale evaluation pipelines, and observability infrastructure, requiring collaboration with engineers to ensure quality.

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

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.

Develop and optimize computer vision models for drones, improve ML pipelines, collaborate on R&D, and tackle advanced technical challenges.

Design and deploy machine learning models for creating HD maps, utilizing advanced ML techniques and collaborating with other teams to deliver reliable solutions.

Develop machine learning models and infrastructure for assessing autonomous vehicle behavior. Collaborate across teams to optimize production systems and model performance.

Join an AI residency to prototype ML and AI solutions for business process optimization, build data pipelines and large-scale analyses, collaborate cross-functionally, evaluate project value chains and risks, and engage with the resident community while advancing research on agentic systems and LLM-based workflows.

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.

Build and optimize large-scale user behavior and conversion models to improve ad ranking, bidding, and recommendations. Monitor model performance, address data quality or degradation, write maintainable code, participate in reviews, and collaborate with cross-functional partners.

As a Machine Learning Engineer, you will design core platforms for autonomous agents, engineer data systems, build tools, and enhance product experience while collaborating with data scientists to deploy advanced models.

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

Lead initiatives to enhance the ML platform, mentor junior engineers, build scalable ML models, and ensure code quality while driving innovation in a startup 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.

Develop and implement online mapping models and algorithms for robotics, focusing on machine learning and data management within uncertain environments.

Design and develop machine learning infrastructure, enhancing core components for model training, monitoring, and serving. Collaborate with ML engineers on robust pipelines.

The Machine Learning Engineer will build data pipelines, contribute to distributed ML workflows and ensure reliability and efficiency of ML systems.

As a Full-Cycle Technical Recruiter, you will manage recruiting from sourcing to closing while enhancing candidate experience and relationships. You will partner with hiring managers, perform analysis, and optimize search strategies.

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.