13 of 13 Remote/Hybrid Ray Jobs

Comfortable collaborating with cross-functional technical partners. Curious, proactive, and eager to learn. Nice to Have: Experience with big data tools (e.g., Apache Spark, Ray). Familiarity with cloud infrastructure (AWS, Terraform, Kubernetes). Knowledge of ML frameworks (Huggingface, PyTorch, TensorFlow, Keras). We use Covey as part ...

certification within the first 90 days of employment Highly preferred: Experience with ML model serving and inference platforms such as Triton Inference Server, KServe, Ray Serve, vLLM, or similar technologies Experience with secure and compliant deployment practices in regulated or government environments Experience with Kubernetes-based ML platforms such ...

Learning pipelines or integrating AI models into production engineering systems.- Experience with large-scale data processing systems and orchestration framework (e.g., Apache Spark, Airflow, Ray, Kafka).- Open-minded and collaborative team player with strong willingness to help others.The US yearly salary range for this role ...

Learning pipelines or integrating AI models into production engineering systems.- Experience with large-scale data processing systems and orchestration framework (e.g., Apache Spark, Airflow, Ray, Kafka).- Open-minded and collaborative team player with strong willingness to help others.The US yearly salary range for this role ...

Learning pipelines or integrating AI models into production engineering systems.- Experience with large-scale data processing systems and orchestration framework (e.g., Apache Spark, Airflow, Ray, Kafka).- Open-minded and collaborative team player with strong willingness to help others.The US yearly salary range for this role ...

Master's in CS, EE, or related field (or equivalent practical experience). Preferred: Contributions to inference frameworks (vLLM, Triton, TensorRT-LLM, Ray Serve, TorchServe). Experience with CUDA kernels, NCCL/SHARP, RDMA/NUMA, or GPU interconnect topologies. Leading multi-team initiatives or partnering with customers on mission ...

track record improving tail latency (P95/P99) and service reliability through metrics-driven work. Preferred: Contributions to inference frameworks (vLLM, Triton, TensorRT-LLM, Ray Serve, TorchServe). Experience with CUDA kernels, NCCL/SHARP, RDMA/NUMA, or GPU interconnect topologies. Leading multi-team initiatives or partnering with customers ...

About the role: Implement well-scoped features and fixes in Python/Go/C++ for model-serving services (e.g., Triton, vLLM, TensorRT-LLM, Ray Serve). Write tests, code comments, and short design docs; participate in code reviews. Add basic metrics and dashboards; assist with alarms and runbooks. Follow ...

improve service reliability and performance using metrics (P95/P99 latency, throughput, error budgets). Preferred Familiarity with orchestration and workflow technologies such as Ray, Kubeflow, Kueue, Istio, Knative, or Argo Workflows Experience with distributed workloads, GPU-based applications, or ML pipelines. Knowledge of scheduling concepts like quota enforcement ...

cross-team architecture. Bachelor's or Master's degree in CS, EE, or related field. Preferred Familiarity with orchestration and workflow technologies such as Ray, Kubeflow, Kueue, Istio, Knative, or Argo Workflows Deep expertise in Slurm/Kubernetes internals. Experience with distributed workloads, GPU-based applications, or ML pipelines. Knowledge ...

company doing large-scale training. Familiarity with agentic AI: RL training with rollouts, agent evaluation, sandbox isolation for running untrusted code. Background with Slurm, Ray, or similar workload orchestration. Opinions on where they fall short. Experience with container runtimes, isolation (gVisor, Kata), or serverless platforms. OSS contributions to Kubernetes SIGs … Ray, PyTorch, or similar. Wondering if you're a good fit? We believe in investing in our people and value candidates who can bring their diverse experiences to our teams - even if you aren't a 100% skill or experience match. Why CoreWeave? At CoreWeave, we work hard, have ...

company doing large-scale training. Familiarity with agentic AI: RL training with rollouts, agent evaluation, sandbox isolation for running untrusted code. Background with Slurm, Ray, or similar workload orchestration. Opinions on where they fall short. Experience with container runtimes, isolation (gVisor, Kata), or serverless platforms. OSS contributions to Kubernetes SIGs … Ray, PyTorch, or similar. Wondering if you're a good fit? We believe in investing in our people and value candidates who can bring their diverse experiences to our teams - even if you aren't a 100% skill or experience match. Why CoreWeave? At CoreWeave, we work hard, have ...

native platform for admitting, scheduling, and operating AI workloads at scale. This platform integrates multiple orchestration and scheduling frameworks such as Kueue, Volcano, and Ray to support modern AI training and inference workflows. It complements SUNK (Slurm on Kubernetes) by providing a Kubernetes-first, cloud-native orchestration layer with deep … operational metrics Comfortable owning services in production and participating in on-call rotations Preferred: Experience with Kubernetes-native orchestration frameworks such as Kueue, Volcano, Ray, Kubeflow, or Argo Workflows Familiarity with GPU-based workloads, ML training, or inference pipelines Knowledge of scheduling concepts such as quota enforcement, pre-emption ...