"hardware accelerators" Jobs
189 open tech roles matching “hardware accelerators”, 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 189 results
Own the end-to-end execution of custom silicon for AI systems at Anthropic, driving external partnerships and program management.
Join Anthropic as a Performance Engineer to optimize AI inference systems for throughput, latency, reliability, and correctness.
Join World Labs as a Performance Engineer to optimize AI models for speed and efficiency in a cutting-edge research environment.
Manage and optimize hardware labs to support various teams and projects at Anthropic, ensuring functionality and readiness.
Lead the capacity management for Baseten's TPU fleet, ensuring optimal performance and reliability in AI workloads.
Join Anthropic as a Product Engineer to oversee hardware production and ensure quality in manufacturing operations.
Join Databricks as a Senior Software Engineer to build and scale a managed GPU training platform for AI models.
Join Inferact as a co-op student to work on cutting-edge AI inference systems in a hands-on engineering role.
Join Databricks as a Staff Software Engineer to drive the architecture of a managed GPU training platform for large-scale AI models.
Join Anthropic's Inference team to design and maintain distributed systems that serve AI models to millions of users worldwide.
Join Neuralink as a Signal Processing Engineer to develop advanced DSP algorithms for brain-computer interface devices.
Join Anthropic as a Staff Software Engineer to enhance deployment infrastructure for AI systems in a collaborative environment.
Join Anthropic's Inference team to design and maintain distributed systems serving AI models to millions globally.
Join Neuralink as an Analog IC Layout Engineer to innovate in chip design for brain-computer interfaces.
Join CoreWeave as an Applied AI Engineer to enhance the performance of our inference platform through benchmarking and optimization.
Lead the engineering organization at Inferact to develop systems for vLLM, focusing on GPU performance and ML systems optimization.
Join Inferact as a cluster administration engineer to manage high-performance GPU compute infrastructure for AI inference.