1 to 25 of 51 Permanent Ray Jobs

/CD , Git-based workflows, and automation Strong problem-solving skills and a collaborative mindset Bonus Terraform or other IaC tools Slurm, Kueue, Ray, Spark, or similar systems GPU tooling (CUDA, Nvidia operators, schedulers) Experience supporting ML training or data science teams ...

workloads (Docker, Kubernetes, Kubeflow, etc.) and integrating with CI/CD tools (Jenkins, GitHub Actions, GitLab CI). Familiarity with distributed computing frameworks (Spark, Ray, TensorFlow Distributed, PyTorch Distributed). Strong understanding of monitoring, logging, and observability for large-scale ML systems. Experience in cost optimisation for compute/ ...

workloads (Docker, Kubernetes, Kubeflow, etc.) and integrating with CI/CD tools (Jenkins, GitHub Actions, GitLab CI). Familiarity with distributed computing frameworks (Spark, Ray, TensorFlow Distributed, PyTorch Distributed). Strong understanding of monitoring, logging, and observability for large-scale ML systems. Experience in cost optimisation for compute/ ...

workloads (Docker, Kubernetes, Kubeflow, etc.) and integrating with CI/CD tools (Jenkins, GitHub Actions, GitLab CI). Familiarity with distributed computing frameworks (Spark, Ray, TensorFlow Distributed, PyTorch Distributed). Strong understanding of monitoring, logging, and observability for large-scale ML systems. Experience in cost optimisation for compute/ ...

workloads (Docker, Kubernetes, Kubeflow, etc.) and integrating with CI/CD tools (Jenkins, GitHub Actions, GitLab CI). Familiarity with distributed computing frameworks (Spark, Ray, TensorFlow Distributed, PyTorch Distributed). Strong understanding of monitoring, logging, and observability for large-scale ML systems. Experience in cost optimisation for compute/ ...

Familiarity with ethical AI, bias mitigation, and regulatory compliance in model development. Strong programming skills in Python and experience with distributed systems (e.g., Kubernetes, Ray). Important information for candidates Recruitment scams have become increasingly common. To protect yourself, please keep the following in mind when applying for roles : Apply ...

about twenty machine learning scientists. The team is supported by an ML Ops team that provides state-of-the-art tooling (including AWS, Encord, Ray, PyTorch Lightning and Weights & Biases). The Applied Science team works closely with product engineering to deploy models to serve our worldwide customer base. Position ...

about twenty machine learning scientists. The team is supported by an ML Ops team that provides state-of-the-art tooling (including AWS, Encord, Ray, PyTorch Lightning and Weights & Biases). The Applied Science team works closely with product engineering to deploy models to serve our worldwide customer base. Position ...

about twenty machine learning scientists. The team is supported by an ML Ops team that provides state-of-the-art tooling (including AWS, Encord, Ray, PyTorch Lightning and Weights & Biases). The Applied Science team works closely with product engineering to deploy models to serve our worldwide customer base. Position ...

about twenty machine learning scientists. The team is supported by an ML Ops team that provides state-of-the-art tooling (including AWS, Encord, Ray, PyTorch Lightning and Weights & Biases). The Applied Science team works closely with product engineering to deploy models to serve our worldwide customer base. Position ...

expertise in C Rust/Go for systems programming, plus Python for model integration. Strong knowledge of distributed runtimes and scheduling frameworks (e.g. Ray, Dask, MPI, or custom equivalents). Experience with GPU cluster management (CUDA, NCCL, Triton Inference Server) and performance tuning across accelerators. Solid grasp of cloud-native ...

fine-tuning large models (LLMs or vision models) Proficiency with PyTorch, JAX, or TensorFlow Experience with distributed training frameworks (DeepSpeed, FSDP, Megatron, ZeRO, Ray) Strong software engineering skills — writing robust, production-grade systems Experience with GPU optimization: memory efficiency, quantization, mixed precision Comfortable owning ambiguous, zero-to-one technical problems … Experience with RLHF pipelines (PPO, DPO, ORPO) Experience training or deploying multimodal or diffusion models Experience in large-scale data processing (Apache Arrow, Spark, Ray) Prior work in a research lab (Google Brain, DeepMind, FAIR, Anthropic, OpenAI ...

fine-tuning large models (LLMs or vision models) Proficiency with PyTorch, JAX, or TensorFlow Experience with distributed training frameworks (DeepSpeed, FSDP, Megatron, ZeRO, Ray) Strong software engineering skills - writing robust, production-grade systems Experience with GPU optimization: memory efficiency, quantization, mixed precision Comfortable owning ambiguous, zero-to-one technical problems … Experience with RLHF pipelines (PPO, DPO, ORPO) Experience training or deploying multimodal or diffusion models Experience in large-scale data processing (Apache Arrow, Spark, Ray) Prior work in a research lab (Google Brain, DeepMind, FAIR, Anthropic, OpenAI) What You'll Get Extreme ownership and autonomy from day one - you define ...

fine-tuning large models (LLMs or vision models) Proficiency with PyTorch, JAX, or TensorFlow Experience with distributed training frameworks (DeepSpeed, FSDP, Megatron, ZeRO, Ray) Strong software engineering skills — writing robust, production-grade systems Experience with GPU optimization: memory efficiency, quantization, mixed precision Comfortable owning ambiguous, zero-to-one technical problems … Experience with RLHF pipelines (PPO, DPO, ORPO) Experience training or deploying multimodal or diffusion models Experience in large-scale data processing (Apache Arrow, Spark, Ray) Prior work in a research lab (Google Brain, DeepMind, FAIR, Anthropic, OpenAI ...

fine-tuning large models (LLMs or vision models) Proficiency with PyTorch, JAX, or TensorFlow Experience with distributed training frameworks (DeepSpeed, FSDP, Megatron, ZeRO, Ray) Strong software engineering skills — writing robust, production-grade systems Experience with GPU optimization: memory efficiency, quantization, mixed precision Comfortable owning ambiguous, zero-to-one technical problems … Experience with RLHF pipelines (PPO, DPO, ORPO) Experience training or deploying multimodal or diffusion models Experience in large-scale data processing (Apache Arrow, Spark, Ray) Prior work in a research lab (Google Brain, DeepMind, FAIR, Anthropic, OpenAI ...

fine-tuning large models (LLMs or vision models) Proficiency with PyTorch, JAX, or TensorFlow Experience with distributed training frameworks (DeepSpeed, FSDP, Megatron, ZeRO, Ray) Strong software engineering skills — writing robust, production-grade systems Experience with GPU optimization: memory efficiency, quantization, mixed precision Comfortable owning ambiguous, zero-to-one technical problems … Experience with RLHF pipelines (PPO, DPO, ORPO) Experience training or deploying multimodal or diffusion models Experience in large-scale data processing (Apache Arrow, Spark, Ray) Prior work in a research lab (Google Brain, DeepMind, FAIR, Anthropic, OpenAI ...

fine-tuning large models (LLMs or vision models) Proficiency with PyTorch, JAX, or TensorFlow Experience with distributed training frameworks (DeepSpeed, FSDP, Megatron, ZeRO, Ray) Strong software engineering skills — writing robust, production-grade systems Experience with GPU optimization: memory efficiency, quantization, mixed precision Comfortable owning ambiguous, zero-to-one technical problems … Experience with RLHF pipelines (PPO, DPO, ORPO) Experience training or deploying multimodal or diffusion models Experience in large-scale data processing (Apache Arrow, Spark, Ray) Prior work in a research lab (Google Brain, DeepMind, FAIR, Anthropic, OpenAI ...

fine-tuning large models (LLMs or vision models) Proficiency with PyTorch, JAX, or TensorFlow Experience with distributed training frameworks (DeepSpeed, FSDP, Megatron, ZeRO, Ray) Strong software engineering skills — writing robust, production-grade systems Experience with GPU optimization: memory efficiency, quantization, mixed precision Comfortable owning ambiguous, zero-to-one technical problems … Experience with RLHF pipelines (PPO, DPO, ORPO) Experience training or deploying multimodal or diffusion models Experience in large-scale data processing (Apache Arrow, Spark, Ray) Prior work in a research lab (Google Brain, DeepMind, FAIR, Anthropic, OpenAI ...

fine-tuning large models (LLMs or vision models) Proficiency with PyTorch, JAX, or TensorFlow Experience with distributed training frameworks (DeepSpeed, FSDP, Megatron, ZeRO, Ray) Strong software engineering skills — writing robust, production-grade systems Experience with GPU optimization: memory efficiency, quantization, mixed precision Comfortable owning ambiguous, zero-to-one technical problems … Experience with RLHF pipelines (PPO, DPO, ORPO) Experience training or deploying multimodal or diffusion models Experience in large-scale data processing (Apache Arrow, Spark, Ray) Prior work in a research lab (Google Brain, DeepMind, FAIR, Anthropic, OpenAI ...

fine-tuning large models (LLMs or vision models) Proficiency with PyTorch, JAX, or TensorFlow Experience with distributed training frameworks (DeepSpeed, FSDP, Megatron, ZeRO, Ray) Strong software engineering skills — writing robust, production-grade systems Experience with GPU optimization: memory efficiency, quantization, mixed precision Comfortable owning ambiguous, zero-to-one technical problems … Experience with RLHF pipelines (PPO, DPO, ORPO) Experience training or deploying multimodal or diffusion models Experience in large-scale data processing (Apache Arrow, Spark, Ray) Prior work in a research lab (Google Brain, DeepMind, FAIR, Anthropic, OpenAI ...

fine-tuning large models (LLMs or vision models) Proficiency with PyTorch, JAX, or TensorFlow Experience with distributed training frameworks (DeepSpeed, FSDP, Megatron, ZeRO, Ray) Strong software engineering skills — writing robust, production-grade systems Experience with GPU optimization: memory efficiency, quantization, mixed precision Comfortable owning ambiguous, zero-to-one technical problems … Experience with RLHF pipelines (PPO, DPO, ORPO) Experience training or deploying multimodal or diffusion models Experience in large-scale data processing (Apache Arrow, Spark, Ray) Prior work in a research lab (Google Brain, DeepMind, FAIR, Anthropic, OpenAI ...

fine-tuning large models (LLMs or vision models) Proficiency with PyTorch, JAX, or TensorFlow Experience with distributed training frameworks (DeepSpeed, FSDP, Megatron, ZeRO, Ray) Strong software engineering skills — writing robust, production-grade systems Experience with GPU optimization: memory efficiency, quantization, mixed precision Comfortable owning ambiguous, zero-to-one technical problems … Experience with RLHF pipelines (PPO, DPO, ORPO) Experience training or deploying multimodal or diffusion models Experience in large-scale data processing (Apache Arrow, Spark, Ray) Prior work in a research lab (Google Brain, DeepMind, FAIR, Anthropic, OpenAI ...

fine-tuning large models (LLMs or vision models) Proficiency with PyTorch, JAX, or TensorFlow Experience with distributed training frameworks (DeepSpeed, FSDP, Megatron, ZeRO, Ray) Strong software engineering skills — writing robust, production-grade systems Experience with GPU optimization: memory efficiency, quantization, mixed precision Comfortable owning ambiguous, zero-to-one technical problems … Experience with RLHF pipelines (PPO, DPO, ORPO) Experience training or deploying multimodal or diffusion models Experience in large-scale data processing (Apache Arrow, Spark, Ray) Prior work in a research lab (Google Brain, DeepMind, FAIR, Anthropic, OpenAI ...

fine-tuning large models (LLMs or vision models) Proficiency with PyTorch, JAX, or TensorFlow Experience with distributed training frameworks (DeepSpeed, FSDP, Megatron, ZeRO, Ray) Strong software engineering skills — writing robust, production-grade systems Experience with GPU optimization: memory efficiency, quantization, mixed precision Comfortable owning ambiguous, zero-to-one technical problems … Experience with RLHF pipelines (PPO, DPO, ORPO) Experience training or deploying multimodal or diffusion models Experience in large-scale data processing (Apache Arrow, Spark, Ray) Prior work in a research lab (Google Brain, DeepMind, FAIR, Anthropic, OpenAI ...

fine-tuning large models (LLMs or vision models) Proficiency with PyTorch, JAX, or TensorFlow Experience with distributed training frameworks (DeepSpeed, FSDP, Megatron, ZeRO, Ray) Strong software engineering skills — writing robust, production-grade systems Experience with GPU optimization: memory efficiency, quantization, mixed precision Comfortable owning ambiguous, zero-to-one technical problems … Experience with RLHF pipelines (PPO, DPO, ORPO) Experience training or deploying multimodal or diffusion models Experience in large-scale data processing (Apache Arrow, Spark, Ray) Prior work in a research lab (Google Brain, DeepMind, FAIR, Anthropic, OpenAI ...