168 results for Machine Learning Engineer Jobs in Mountain View, CA, US

Company OverviewDyna Robotics is at the forefront of revolutionizing robotic manipulation with cutting-edge foundation models. Our mission is to empower businesses by automating repetitive, stationary tasks with affordable, intelligent robotic arms. Leveraging the latest advancements in foundation m...

Contribute to the Inference Enablement Team by developing foundational technology and frameworks for optimizing model architectures on diverse hardware platforms, including CPU, GPU, and custom Silicon. Engage in building model publishing frameworks at scale for various applications such as Ads and ...

Responsible for building and augmenting Machine Learning models for computer vision, updating and scaling ML pipelines, implementing models using Pytorch and Tensorflow, and optimizing performance. Involves end-to-end processes from data gathering to model deployment and troubleshooting.

Responsible for building AI-based services and platforms for machine learning, designing scalable distributed platforms, collaborating with cross-functional teams, and ensuring operational readiness of services. The role requires leadership in ML developer tools and a passion for AI/ML infrastructur...

Propose and conduct novel research for AI chips, translate mathematical operations for performance, develop software performance knowledge, co-design model architectures, and implement frontier models using Python and Rust. Optimize model instructions and implement inference-time acceleration techni...

Gen Z is the generation of the side hustle. 💪🏻 They're creators. 👩‍🎤 They're freelancers. 🧑‍💻 They're investors. 👩‍💼 And they're not afraid to take on challenges, especially when it comes to their finances - and we're here for it.Step is a next-generation financial services company building ...

Design and develop innovative features for back-end systems, collaborate with engineers and product managers, and take ownership of software components while ensuring quality and maintainability.

Responsible for deploying, optimizing, and accelerating machine learning models on various computing platforms, implementing compiler support for inference performance, and ensuring compliance with quality management and regulatory standards.

Lead the development and optimization of the machine learning platform, improve training infrastructure scalability and efficiency, provide tooling for ML practitioners, develop model deployment frameworks, and collaborate with other teams on model developments.

Responsible for architecting, building, and deploying ML systems and services for a data curation platform. Design and implement large-scale data pipelines, partner with researchers to integrate new features, and ensure system reliability and security.