"distributed training frameworks" Jobs
208 open tech roles matching “distributed training frameworks”, taken straight from company career pages — not reposted from other job boards. Most in demand right now: Python, AWS, AI/ML. Every listing is re-checked daily and closed roles are removed.
Showing 20 of 208 results
Lead a high-performing engineering team at Databricks to enhance the AI Runtime product for GPU training infrastructure.
Join Abridge as a Machine Learning Infrastructure Engineer to optimize AI model inference infrastructure in a fast-paced healthcare startup.
Join Hedra as a Research Engineer to lead the development of action-conditioned world models in a pioneering Physical AI team.
Join Krea.ai as a Machine Learning Engineer to work on innovative AI tools for creatives in a collaborative environment.
Join Strava as a Staff AI Engineer to build AI-powered features for millions of athletes worldwide.
Lead a team of engineers to build infrastructure for training and evaluating ML models in a flat, innovative organization.
Join Cursor as a Software Engineer on the ML Platform to build infrastructure that enhances machine learning models and supports product engineers.
Join Xaira Therapeutics as a Senior Software Engineer to build AI infrastructure for drug discovery and development.
Lead the development of next-generation multimodal models at Twelve Labs, impacting thousands of customers worldwide.
Join World Labs as a Performance Engineer to optimize AI models for speed and efficiency in a cutting-edge research environment.
Join Genmo as a Research Scientist to lead initiatives in alignment and post-training for large-scale video generation models.
Join Databricks as a Senior Applied ML Engineer to optimize infrastructure and enhance serverless compute products.
Join Anthropic as a Staff Software Engineer to design APIs and frameworks for reinforcement learning environments in a collaborative AI research team.
Join Databricks as a Senior Software Engineer to build infrastructure for AI applications and improve distributed AI workloads.
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