Forward Deployed Engineer - AI/ML Platforms

Responsibilities

• Design and implement production-grade AI platform architectures on Kubernetes and public cloud infrastructure (AWS, Azure, and GCP).
• Partner directly with customer platform, infrastructure, and ML engineering teams to deploy, operate, and optimize distributed AI workloads.
• Lead implementation engagements including platform installation, networking, security, observability, scaling, and upgrades.
• Troubleshoot complex distributed systems issues spanning infrastructure, Kubernetes, networking, storage, and AI applications.
• Develop automation, tooling, reference implementations, and infrastructure-as-code to accelerate customer success.
• Collaborate with Product and Engineering teams to communicate customer requirements and shape future platform capabilities.

Requirements

• 5+ years of experience in cloud infrastructure, platform engineering, DevOps, SRE, or software engineering.
• Experience building, deploying, or operating ML/AI platforms for model training, inference, or large-scale data processing.
• Strong expertise with Kubernetes and containerized production environments.
• Proficiency in operating cloud infrastructure on AWS, Azure, or GCP, including networking, security, and IAM.
• Experience with Infrastructure as Code and modern DevOps tooling such as Terraform, Helm, GitOps, or CI/CD pipelines.
• Strong software engineering skills in Python, Go, Java, or a comparable language.
• Experience in customer-facing engineering roles such as consulting, professional services, or solutions architecture.
• Excellent communication skills with the ability to engage both executive and deeply technical stakeholders.

Preferred Qualifications

• Familiarity with distributed computing frameworks such as Ray, Spark, Dask, or Kubernetes-native distributed systems.
• Willingness to travel as needed to work alongside strategic customers.

About the Company

Anyscale is on a mission to democratize distributed computing and make it accessible to software developers of all skill levels. We are commercializing Ray, a popular open-source project that creates an ecosystem of libraries for scalable machine learning. Companies like OpenAI, Uber, and Spotify use Ray to accelerate the progress of AI applications in the real world.