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 ❯
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 ❯
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 ❯
hybrid HPC environments. Proficiency in Kubernetes, Docker, Terraform (or equivalent infrastructure automation tools), and cloud services (AWS, GCP, Azure). Deep experience with ML workflow orchestration tools (e.g., Kubeflow, Ray, Airflow, Metaflow). Excellent programming skills in Python; experience with Bash, Go, or C++ is beneficial. Strong understanding of ML frameworks (PyTorch, TensorFlow, JAX) and familiarity with distributed training methods More ❯
experiments. Experience with ML model monitoring systems. Experience with ML training and data pipelines and working with distributed systems. Proficiency with modern deep learning libraries and frameworks (PyTorch, Lightning, Ray). Preferred Qualifications Experience owning a product from development through monitoring and incident response. Knowledge of the design, manufacturing, AEC, or media & entertainment industries. Experience with Autodesk or similar products More ❯
features which deliver AI capabilities to some of the biggest names in the insurance industry. We are developing a modern real-time ML platform using technologies like Python, PyTorch, Ray, k8s (helm + flux), Terraform, Postgres and Flink on AWS. We are very big fans of Infrastructure-as-Code and enjoy Agile practices. As a team, we're driven by More ❯
labeled and unlabeled data Qualifications PhD in CS/CE/EE, or equivalent, in industry experience Deep knowledge of PyTorch Knowledge of model training framework (e.g. PyTorch Lightning, ray, etc.) In-depth knowledge of transformer architecture and ways to accelerate the training and inference of transformer models Experience of performing large scale distributed training of models A track record More ❯
required. Below is a detailed breakdown of all the technologies we use. - Backend: Python - Frontend: Typescript and React - Kubernetes for deployment - GCP for underlying infrastructure - Machine Learning: PyTorch, CUDA, Ray We encourage people from all backgrounds, cultures and skill levels to apply. It is okay to not meet all requirements listed as we are looking for individuals who are passionate More ❯
features which deliver AI capabilities to some of the biggest names in the insurance industry. We are developing a modern real-time ML platform using technologies like FastAPI, PyTorch, Ray, k8s (helm + flux), Terraform, Postgres, Flink on AWS, React & Typescript. We operate a fully Python stack except for frontend and infrastructure code. We are very big fans of Infrastructure More ❯
strong software engineering skills. Proficiency in Python and related ML frameworks such as JAX, Pytorch and XLA/MLIR. Experience with distributed training infrastructures (Kubernetes, Slurm) and associated frameworks (Ray). Experience using large-scale distributed training strategies. Hands on experience on training large model at scale. Hands on experience with the post training phase of model training, with a More ❯
and high-profile global clients: Meta . Meta is home to some of the most recognised platforms and technologies in the world-including Facebook, Instagram, WhatsApp, Meta Quest and Ray-Ban Meta smart glasses. As their global media agency of record, we're responsible for helping shape how Meta shows up across markets and media channels worldwide. This is a More ❯
About Anyscale At Anyscale , we're on a mission to democratize distributed computing and make it accessible to software developers of all skill levels. We're commercializing Ray , a popular open-source project that's creating an ecosystem of libraries for scalable machine learning. Companies like OpenAI , Uber , Spotify , Instacart , Cruise , and many more, have Ray in their tech stacks … to accelerate the progress of AI applications out into the real world. With Anyscale, we're building the best place to run Ray, so that any developer or data scientist can scale an ML application from their laptop to the cluster without needing to be a distributed systems expert. Proud to be backed by Andreessen Horowitz, NEA, and Addition with … and Ray. You'll be on point for demoing our product, scoping POVs, making users successful, and amplifying the voice of our customers. Expect to learn a ton about Ray, Anyscale, and early stage product go-to-market! You'll be fundamental in helping us disrupt what it means to build distributed applications at scale. Our product is inherently technical More ❯
