Remote Software engineering Jobs • TensorFlow

Implement state-of-the-art models and techniques, including deep learning architectures and foundation models. Diagnose model performance issues, analyze sources of error and design strategies to mitigate them. Work with scientific and biological data to contribute to projects in drug discovery, life sciences and healthcare. Design and run experiments, critically evaluate results and communicate findings through clear, data-driven reports.

Design, build, and maintain large-scale distributed training infrastructure for Ads ML models. Develop tools and frameworks on top of the Ray platform. Build tools to debug, profile, and tune distributed training jobs for performance and reliability. Integrate with object storage systems and improve data access patterns. Collaborate with ML engineers to improve model training time, efficiency, and GPU training costs. Drive improvements in scheduling, state management, and fault tolerance.

In this role as Sr. Staff Machine Learning Engineer, you will define and lead the architecture and development of large-scale, foundational machine learning systems that power care personalization, treatment intelligence, and automation at scale. Your work will directly shape MedMatch—our AI-powered system—by owning the architecture and direction of key ML components, enhancing provider-patient interactions, optimizing treatment recommendations, and expanding into new verticals.

In this role as Principal Machine Learning Engineer, you will define and drive the architectural vision for large-scale, foundational machine learning models and applications that power care personalization, treatment intelligence, and automation at scale. This impact will be driven by architecting resilient, scalable, and extensible ML platforms that accelerate product development, unlock intelligent care delivery, and influence long-term ML strategy and engineering practices across teams.

As a Senior Machine Learning Engineer at Artera, you'll be a key technical leader driving the development of AI-based biomarkers that personalize cancer therapy. You will design, build, deploy, and continuously improve multimodal models—combining whole-slide images with clinical and molecular data—to predict molecular traits and patient outcomes. You’ll translate clinical needs into robust, well-validated solutions.

Design, build, and maintain large-scale distributed training infrastructure for Ads ML models. Develop tools and frameworks on top of the Ray platform. Build tools to debug, profile, and tune distributed training jobs for performance and reliability. Integrate with object storage systems and improve data access patterns.

Join the Ads team as a Machine Learning Engineer, a key contributor to Reddit’s business. You will be responsible for the full lifecycle of our ML systems, from initial research and modeling to deployment and optimization in production. Your work will directly impact how we deliver relevant ads and drive value for our advertisers across areas like ad ranking, bidding, measurement, and optimization.

As a Machine Learning Engineer at Chartbeat, you will contribute to the design, development, and deployment of machine learning systems at scale. You will also collaborate with product managers and cross-functional engineering teams to deliver ML and generative AI powered features and explore upcoming generative AI technologies to solve complex business challenges.