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About Us: Fireworks is the platform for specialized intelligence, enabling companies to build, train, and serve AI models tailored to their own data, workflows, and products. Founded by the team behind PyTorch and…
About Thinking Machines The mission of Thinking Machines is to build AI that extends human will and judgment. We are training frontier models with Inkling, developing Tinker to let people make models their own, and…
Salary: $100 - $200 p.h. Cleared Recruitment are looking to speak to professionals who hold a TSPV clearance for long-term contract and permanent opportunities within the National Security, Defence, Intelligence,…
Designs and operates AI inference infrastructure in Riyadh, ensuring reliability for ML workloads using Linux, Python, and PyTorch.
Would you like to join a team curious about understanding how foundation models work and to expand their capabilities in scientific domains? We perform and publish novel research and apply our findings to drive product…
Build and fine-tune large language models for healthcare, creating conversational AI that automates claims and improves patient experiences using Python, PyTorch, and cloud ML platforms.
About us AB InBev is the leading global brewer and one of the world’s top 5 consumer product companies. With over 500 beer brands, we’re number one or two in many of the world’s top beer markets, including North…
Build and deploy LLM-powered NLP systems and Agentic AI for customer-experience automation, scaling solutions to millions of daily interactions in a fast-paced startup.
Designs and deploys ML models to predict and prevent GPU cluster failures, optimizing real-time AI infrastructure reliability and utilization.
Design and scale distributed data pipelines and MLOps infrastructure for a GPU-powered AI cloud platform, focusing on reliability, observability, and automated anomaly detection in a Kubernetes environment.
Designs and deploys AI infrastructure solutions for enterprise customers, focusing on LLM workloads and GPU-based cloud platforms.
Senior engineer builds and runs Kubernetes-native benchmarking services to measure latency, throughput, and reliability across CoreWeave’s global AI cloud, publishing results like MLPerf.
Develops and optimizes AI model-serving systems on GPU infrastructure, focusing on latency, reliability, and cost while working with tools like Triton, vLLM, and Kubernetes.
Builds and maintains Kubernetes-native AI research infrastructure for CoreWeave’s customers, focusing on job orchestration, distributed training, and developer tooling to accelerate AI model development.
Write, profile, and optimize CUDA kernels for LLM inference to maximize throughput and minimize latency on NVIDIA GPUs, using DSLs like Triton or Mojo and benchmarking with MLPerf.
Research and build continuous learning systems for self-improving AI agents on the OpenPipe team. You'll investigate RLHF, reward modeling, and on-policy distillation to solve production bottlenecks in agent training. Core stack uses PyTorch/JAX for model training with Kubernetes and Megatron for distributed GPU infrastructure.
Applied AI Engineer, Inference at CoreWeave. Improve real-world performance of AI models via benchmarking, profiling, and optimization.
Design and deliver AI infrastructure demos and proofs-of-concept for new customers, partnering with sales and engineering to onboard greenfield AI teams onto CoreWeave’s GPU-powered cloud platform.
Build and optimize AI infrastructure performance monitoring tools, ensuring high availability and observability for CoreWeave’s cloud platform.
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