"ai workloads" Jobs
523 open tech roles matching “ai workloads”, taken straight from company career pages — not reposted from other job boards. Most in demand right now: Python, Kubernetes, AI/ML. Every listing is re-checked daily and closed roles are removed.
Showing 20 of 523 results
Join Inferact as a co-op student to work on cutting-edge AI inference systems in a hands-on engineering role.
Join the Infrastructure team to build and operate foundational systems that support Perplexity’s products.
Join Anthropic's Inference team to design and maintain distributed systems serving AI models to millions globally.
Lead a team of Solutions Architects to manage complex customer deployments across various cloud environments.
Join Perplexity AI as a Technical Staff member to enhance our AI inference engine with cutting-edge technologies.
Join Baseten as a Forward Deployed Engineer to solve complex AI challenges for leading companies.
Join Anthropic as a Performance Engineer to optimize the inference engine for AI systems at scale.
Own the strategy and execution for CoreWeave's data services portfolio, shaping the future of data in AI cloud environments.
Lead the Runtime Fabric team at Baseten to build container runtimes tailored for AI inference workloads.
Join Anthropic as a Demand Planning expert to optimize AI infrastructure capacity and ensure timely delivery across multiple platforms.
Join Baseten as a GPU Kernel Engineer to optimize high-performance GPU kernels for cutting-edge AI applications.
Join CoreWeave as a Staff Software Engineer to own the reliability and performance of our Kubernetes-based data platform.
Lead the infrastructure for AI computing services at CoreWeave, driving innovation and managing high-performing engineering teams.
Join Mirendil as a staff engineer to design and optimize custom ML kernels for frontier AI research.
Join Atoms as a Staff Cluster Infrastructure Engineer to optimize and manage GPU compute clusters for real-world AI applications.
Join Databricks as a Staff Software Engineer to drive the architecture of a managed GPU training platform for large-scale AI models.