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 ❯
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 (CAD 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 ❯
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 ❯
user base. As a team, we are a collaborative, cross-functional group with backgrounds in information retrieval, natural language processing, and distributed systems. We work with Go microservices, Python, Ray Serve, Kubernetes/KubeRay, and work on AWS, GCP & Azure. We provide thought leadership across a variety of mediums including open code repositories, publishing blogs, and speaking at conferences. We … Bring 5+ years working in an MLOps or related ML Engineering role Production experience self-hosting & operating LLMs at scale for generative tasks via an inference framework such as Ray or KServe (or similar) Production experience with running and tuning specialized hardware for Generative AI workloads, especially GPUs via CUDA Measured and articulate written and spoken communication skills. You work More ❯
