1 to 25 of 43 Remote Ray Jobs

environments) Hands-on with Docker, Kubernetes, and Terraform Strong scripting skills in Python or Bash Familiar with ML lifecycle tools, model monitoring, and versioning Exposure to tools like KServe, Ray Serve, Triton, or vLLM a big plus Bonus Points: Experience with observability frameworks like Prometheus or OpenTelemetry Knowledge of ML libraries: TensorFlow, PyTorch, HuggingFace Exposure to Azure or GCP Passion More ❯

environments) Hands-on with Docker, Kubernetes, and Terraform Strong scripting skills in Python or Bash Familiar with ML lifecycle tools, model monitoring, and versioning Exposure to tools like KServe, Ray Serve, Triton, or vLLM a big plus Bonus Points: Experience with observability frameworks like Prometheus or OpenTelemetry Knowledge of ML libraries: TensorFlow, PyTorch, HuggingFace Exposure to Azure or GCP Passion More ❯

environments) Hands-on with Docker, Kubernetes, and Terraform Strong scripting skills in Python or Bash Familiar with ML lifecycle tools, model monitoring, and versioning Exposure to tools like KServe, Ray Serve, Triton, or vLLM is a big plus Bonus Points Experience with observability frameworks like Prometheus or OpenTelemetry Knowledge of ML libraries: TensorFlow, PyTorch, HuggingFace Exposure to Azure or GCP More ❯

paced, collaborative, and dynamic environment. Nice to haves: Prior experience with PCB design, EDA tools, or related optimization problems. Hands-on experience in high-performance computing environments (e.g., Kubernetes, Ray, Dask). Contributions to open-source projects, publications, or top placements in ML competitions (e.g., Kaggle). Expertise in related fields such as Computer Vision, Representation Learning, or Simulation Environments. More ❯

paced, collaborative, and dynamic environment. Nice to haves: Prior experience with PCB design, EDA tools, or related optimization problems. Hands-on experience in high-performance computing environments (e.g., Kubernetes, Ray, Dask). Contributions to open-source projects, publications, or top placements in ML competitions (e.g., Kaggle). Expertise in related fields such as Computer Vision, Representation Learning, or Simulation Environments. More ❯

processing skills with varied unstructured data representations Processing unstructured data, such as 3D geometric data Large scale, data-intensive systems in production Distributed computing frameworks, such as Spark, Dask, Ray Data etc. Cloud platforms such as AWS, Azure, or GCP Docker Documenting code, architectures, and experiments Linux systems and bash terminals Preferred Qualifications Databases and/or data warehousing technologies More ❯

GCP Containerization technologies, such as Docker and Kubernetes Documenting code, architectures, and experiments Linux systems and bash terminals Preferred Qualifications Hands-on experience with: Distributed computing frameworks, such as Ray Data and Spark. Databases and/or data warehousing technologies, such as Apache Hive. Data transformation via SQL and DBT. Orchestration platforms, such as Apache Airflow. Data catalogs and metadata … GCP Containerization technologies, such as Docker and Kubernetes Documenting code, architectures, and experiments Linux systems and bash terminals Preferred Qualifications Hands-on experience with: Distributed computing frameworks, such as Ray Data and Spark. Databases and/or data warehousing technologies, such as Apache Hive. Data transformation via SQL and DBT. Orchestration platforms, such as Apache Airflow. Data catalogs and metadata More ❯

for GCP. Expertise in Terraform and infrastructure-as-code practices. Solid experience deploying workloads with Kubernetes, including cluster and node management. Familiarity with ML workload orchestration using Docker, Kubeflow, Ray, or similar tools. Skilled in Python and comfortable working with SQL and data processing tools. Understanding of the machine learning lifecycle from data ingestion to inference. Experience handling large-scale More ❯

for GCP. Expertise in Terraform and infrastructure-as-code practices. Solid experience deploying workloads with Kubernetes, including cluster and node management. Familiarity with ML workload orchestration using Docker, Kubeflow, Ray, or similar tools. Skilled in Python and comfortable working with SQL and data processing tools. Understanding of the machine learning lifecycle from data ingestion to inference. Experience handling large-scale More ❯

for GCP. Expertise in Terraform and infrastructure-as-code practices. Solid experience deploying workloads with Kubernetes, including cluster and node management. Familiarity with ML workload orchestration using Docker, Kubeflow, Ray, or similar tools. Skilled in Python and comfortable working with SQL and data processing tools. Understanding of the machine learning lifecycle from data ingestion to inference. Experience handling large-scale More ❯

for GCP. Expertise in Terraform and infrastructure-as-code practices. Solid experience deploying workloads with Kubernetes, including cluster and node management. Familiarity with ML workload orchestration using Docker, Kubeflow, Ray, or similar tools. Skilled in Python and comfortable working with SQL and data processing tools. Understanding of the machine learning lifecycle from data ingestion to inference. Experience handling large-scale More ❯

for GCP. Expertise in Terraform and infrastructure-as-code practices. Solid experience deploying workloads with Kubernetes, including cluster and node management. Familiarity with ML workload orchestration using Docker, Kubeflow, Ray, or similar tools. Skilled in Python and comfortable working with SQL and data processing tools. Understanding of the machine learning lifecycle from data ingestion to inference. Experience handling large-scale More ❯

for GCP. Expertise in Terraform and infrastructure-as-code practices. Solid experience deploying workloads with Kubernetes, including cluster and node management. Familiarity with ML workload orchestration using Docker, Kubeflow, Ray, or similar tools. Skilled in Python and comfortable working with SQL and data processing tools. Understanding of the machine learning lifecycle from data ingestion to inference. Experience handling large-scale More ❯

for GCP. Expertise in Terraform and infrastructure-as-code practices. Solid experience deploying workloads with Kubernetes, including cluster and node management. Familiarity with ML workload orchestration using Docker, Kubeflow, Ray, or similar tools. Skilled in Python and comfortable working with SQL and data processing tools. Understanding of the machine learning lifecycle from data ingestion to inference. Experience handling large-scale More ❯

for GCP. Expertise in Terraform and infrastructure-as-code practices. Solid experience deploying workloads with Kubernetes, including cluster and node management. Familiarity with ML workload orchestration using Docker, Kubeflow, Ray, or similar tools. Skilled in Python and comfortable working with SQL and data processing tools. Understanding of the machine learning lifecycle from data ingestion to inference. Experience handling large-scale More ❯

for GCP. Expertise in Terraform and infrastructure-as-code practices. Solid experience deploying workloads with Kubernetes, including cluster and node management. Familiarity with ML workload orchestration using Docker, Kubeflow, Ray, or similar tools. Skilled in Python and comfortable working with SQL and data processing tools. Understanding of the machine learning lifecycle from data ingestion to inference. Experience handling large-scale More ❯

for GCP. Expertise in Terraform and infrastructure-as-code practices. Solid experience deploying workloads with Kubernetes, including cluster and node management. Familiarity with ML workload orchestration using Docker, Kubeflow, Ray, or similar tools. Skilled in Python and comfortable working with SQL and data processing tools. Understanding of the machine learning lifecycle from data ingestion to inference. Experience handling large-scale More ❯

for GCP. Expertise in Terraform and infrastructure-as-code practices. Solid experience deploying workloads with Kubernetes, including cluster and node management. Familiarity with ML workload orchestration using Docker, Kubeflow, Ray, or similar tools. Skilled in Python and comfortable working with SQL and data processing tools. Understanding of the machine learning lifecycle from data ingestion to inference. Experience handling large-scale More ❯

data modeling, architecture, and processing unstructured data. Experience with processing 3D geometric data. Experience with large-scale, data-intensive systems in production. Knowledge of distributed computing frameworks (Spark, Dask, Ray). Experience with cloud platforms (AWS, Azure, GCP). Proficiency with Docker, Linux, and bash. Ability to document code, architectures, and experiments. Preferred Qualifications Experience with databases and data warehousing More ❯

processing skills with varied unstructured data representations · Processing unstructured data, such as 3D geometric data · Large scale, data-intensive systems in production · Distributed computing frameworks, such as Spark, Dask, Ray Data etc. · Cloud platforms such as AWS, Azure, or GCP · Docker · Documenting code, architectures, and experiments · Linux systems and bash terminals Preferred Qualifications o Databases and/or data warehousing More ❯

processing skills with varied unstructured data representations · Processing unstructured data, such as 3D geometric data · Large scale, data-intensive systems in production · Distributed computing frameworks, such as Spark, Dask, Ray Data etc. · Cloud platforms such as AWS, Azure, or GCP · Docker · Documenting code, architectures, and experiments · Linux systems and bash terminals Preferred Qualifications o Databases and/or data warehousing More ❯

processing skills with varied unstructured data representations · Processing unstructured data, such as 3D geometric data · Large scale, data-intensive systems in production · Distributed computing frameworks, such as Spark, Dask, Ray Data etc. · Cloud platforms such as AWS, Azure, or GCP · Docker · Documenting code, architectures, and experiments · Linux systems and bash terminals Preferred Qualifications o Databases and/or data warehousing More ❯

processing skills with varied unstructured data representations · Processing unstructured data, such as 3D geometric data · Large scale, data-intensive systems in production · Distributed computing frameworks, such as Spark, Dask, Ray Data etc. · Cloud platforms such as AWS, Azure, or GCP · Docker · Documenting code, architectures, and experiments · Linux systems and bash terminals Preferred Qualifications o Databases and/or data warehousing More ❯

processing skills with varied unstructured data representations · Processing unstructured data, such as 3D geometric data · Large scale, data-intensive systems in production · Distributed computing frameworks, such as Spark, Dask, Ray Data etc. · Cloud platforms such as AWS, Azure, or GCP · Docker · Documenting code, architectures, and experiments · Linux systems and bash terminals Preferred Qualifications o Databases and/or data warehousing More ❯

processing skills with varied unstructured data representations · Processing unstructured data, such as 3D geometric data · Large scale, data-intensive systems in production · Distributed computing frameworks, such as Spark, Dask, Ray Data etc. · Cloud platforms such as AWS, Azure, or GCP · Docker · Documenting code, architectures, and experiments · Linux systems and bash terminals Preferred Qualifications o Databases and/or data warehousing More ❯