1 to 25 of 30 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 ❯

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 ❯

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 ❯

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 ❯

skills we are searching for are: Programming Skills: Proficiency in Python, data analytics, deep learning (Scikit-learn, Pandas, PyTorch, Jupyter, pipelines), and practical knowledge of data tools like Databricks, Ray, Vector Databases, Kubernetes, and workflow scheduling tools such as Apache Airflow, Dagster, and Astronomer. GPU Computing: Familiarity with GPU computing, both on-premises and on cloud platforms, and experience in More ❯

Rust, Python, Solidity Infrastructure: Kubernetes, Docker, GPU Scheduling (e.g., Kubeflow, Slurm), CI/CD pipelines Blockchain: EVM, Cosmos SDK, ZK/L2 solutions AI Stack (plus): PyTorch, Hugging Face, Ray, ONNX What We Offer Competitive salary + equity/token package Flexible, remote-first work environment High-impact leadership role in a fast-scaling frontier tech company Opportunity to shape More ❯

Rust, Python, Solidity Infrastructure: Kubernetes, Docker, GPU Scheduling (e.g., Kubeflow, Slurm), CI/CD pipelines Blockchain: EVM, Cosmos SDK, ZK/L2 solutions AI Stack (plus): PyTorch, Hugging Face, Ray, ONNX What We Offer Competitive salary + equity/token package Flexible, remote-first work environment High-impact leadership role in a fast-scaling frontier tech company Opportunity to shape More ❯

Pallas, Triton, and/or CUDA code to achieve performance breakthroughs. Required Skills Understanding of Linux systems, performance analysis tools, and hardware optimisation techniques Experience with distributed training frameworks (Ray, Dask, PyTorch Lightning, etc.) Expertise with Python and/or C/C++ Development with machine learning frameworks (JAX, Tensorflow, PyTorch etc.) Passion for profiling, identifying bottlenecks, and delivering efficient More ❯

functional engineering teams. Passion for open-source and decentralized infrastructure. Excellent communication and executive presence. Preferred Tech Stack Languages: Go, Rust, Python, Solidity AI Stack (plus): PyTorch, Hugging Face, Ray, ONNX What We Offer Competitive salary + equity/token package Flexible, remote-first work environment High-impact leadership role in a fast-scaling frontier tech company Opportunity to shape More ❯

Extensive background in delivering production-grade, data-centric applications for quantitative trading and analytics, with demonstrated expertise in: The python data engineering stack (Polars, Parquet, FastAPI, Jupyter, Airflow, Streamlit, Ray) High-performance data stores and query engines (Starburst, Snowflake) Real-time streaming analytics technologies (Kafka, Flink) Cloud container technologies (AWS, Azure, GCP, Docker, Kubernetes) Proven success in enhancing developer experience More ❯

quality datasets suitable for machine learning research and production. High-Performance Data Pipelines Develop and optimize distributed systems for data processing, including filtering, indexing, and retrieval, leveraging frameworks like Ray, Metaflow, Spark, or Hadoop. Synthetic Data Generation Build and orchestrate pipelines to generate synthetic data at scale, advancing research on cost-efficient inference and training strategies. Experiments & Analysis Design and … inference of pretrained models, 3D rendering engines, and/or other softwares. Distributed Computing & MLOps Demonstrated proficiency in setting up large-scale, robust data pipelines, using frameworks like Spark, Ray, or Metaflow. Comfortable with model versioning, and experiment tracking. Performance Optimization Good understanding of parallel and distributed computing. Experienced with setting up evaluation methods Cloud & Storage Systems Experience with AWS More ❯

collaborative, and research-driven environment. Nice to Haves Hands-on experience with PCB design, EDA software, or circuit-level optimization problems. Familiarity with high-performance computing tools like Kubernetes, Ray, or Dask. Open-source contributions, academic publications, or strong performance in ML competitions (e.g., Kaggle). Background in adjacent areas like Computer Vision, Representation Learning, or Simulation Environments. Why Join More ❯

collaborative, and research-driven environment. Nice to Haves Hands-on experience with PCB design, EDA software, or circuit-level optimization problems. Familiarity with high-performance computing tools like Kubernetes, Ray, or Dask. Open-source contributions, academic publications, or strong performance in ML competitions (e.g., Kaggle). Background in adjacent areas like Computer Vision, Representation Learning, or Simulation Environments. Why Join More ❯

high-quality data flows through the pipeline. Collaborate with research to define data quality benchmarks . Optimize end-to-end performance across distributed data processing frameworks (e.g., Apache Spark, Ray, Airflow). Work with infrastructure teams to scale pipelines across thousands of GPUs . Work directly with the leadership on the data team roadmaps. Manage the team of data engineers. More ❯

Ability to convert customer requirements or business challenges into well-defined machine learning solutions We are using many technologies day to day such as various AWS services, GCP, Kubernetes, Ray Serve, Kubeflow, and ReTool. Any experience in these areas would be a bonus Sprout.ai Values Hungry for Growth - Unleash your inner Sprout: Sprouts embrace growth, forget comfort zones, and help More ❯