We are redirecting you to the source. If you are not redirected in 3 seconds, please click here.

ML / AI Enablement Engineer at Anyscale. Remote Location: San Francisco or Palo Alto, CA. 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 $250+ million raised to date.. About the role. We’re looking for a ML / AI Enablement Engineer to help developers and technical teams learn how to build, deploy, and scale modern machine learning and AI systems in production.. This is a unique role for someone with hands-on experience in ML engineering, MLOps, or AI infrastructure who’s passionate about education, enablement, and real-world impact. You’ll design and deliver training materials—ranging from interactive labs and instructor-led workshops to certification programs and short-form videos—that teach the foundational and advanced concepts behind scalable ML/AI systems.. In addition to building educational content, you’ll also serve as an instructor and technical educator, facilitating training sessions and workshops for customers, prospects, and the open source Ray community. You’ll work closely with engineers across these groups to ensure the content you create reflects real-world architectures, production challenges, and best practices, making your work both technically rigorous and immediately useful.. About the team. Our mission is to advance the capabilities of Ray and advance machine learning workloads on the Anyscale Platform. We are a lean and mighty team, responsible for upholding the quality and effectiveness of user documentation spanning long form docs and API references.. We operate at the intersection of customer experience and product development. Uniquely positioned to focus on a holistic customer experience across all products. Trainers are focused on onboarding and self-service, beyond just docs pages, but including understanding critical user journeys, search, and chatbots. . We are the internal advocates of the importance of user documentation, and quality standards. To be successful, our ideal candidate is curious, able to work independently, have strong opinions about our users’ experience, and have a growth mindset.. What You'll Do. Design and develop technical training materials focused on scalable ML/AI engineering workflows, infrastructure, and tooling. Build and maintain hands-on labs, Jupyter notebooks, and project-based assessments covering topics such as distributed training, scalable inference, and AI pipeline orchestration. Serve as a live instructor or facilitator for technical workshops, customer enablement sessions, or community training events. Collaborate with Anyscale engineers, customer teams, and Ray open source contributors to ensure training reflects real production environments and use cases. Develop and maintain certification materials, including exams, project challenges, and evaluation rubrics. Scope and adapt materials for custom training solutions tailored to enterprise or partner-specific needs. Required Experience. 2–5 years of experience in . ML engineering, MLOps, or AI infrastructure roles. Proficient in . Python. and comfortable working with . ML/AI frameworks. such as PyTorch, Hugging Face Transformers, or TensorFlow. Experience with . distributed computing tools or frameworks. (e.g., Ray, Spark, Dask, Kubernetes). Familiarity with modern ML/AI systems topics, including:. Multi-node or multi-GPU training. Model deployment and scalable inference. Workflow orchestration and reproducible pipelines. Strong communication and teaching skills; ability to convey complex ML/AI topics clearly. Comfort with . live technical instruction. , both virtual and in-person. Bonus. Experience designing or contributing to . technical certification programs. Created or delivered . technical enablement content. —e.g., tutorials, courses, internal documentation, or public talks. Familiarity with cloud-native ML/AI services and developer tooling. Participation in open source projects or developer communities in the AI/infra ecosystem. Why join us. Help . educate the next generation of ML/AI engineers. and practitioners. Build and deliver learning programs grounded in . real-world engineering problems. Collaborate with passionate educators, engineers, and community builders. Influence adoption of cutting-edge tools like . Ray. in production ML/AI environments. Competitive salary, equity, full benefits, and flexible remote work culture. At Anyscale, we take a market-based approach to compensation. We are data-driven, transparent, and consistent. As the market data changes over time, the target salary for this role may be adjusted. . This role is also eligible to participate in Anyscale's Equity and Benefits offerings, including the following:. Stock Options. Healthcare plans, with premiums covered by Anyscale at 99% for both employees and dependents. 401k Retirement Plan. Education & Wellbeing Stipend. Paid Parental Leave. Fertility Benefits. Paid Time Off. Commute reimbursement. 100% of in-office meals covered. Anyscale Inc. is an Equal Opportunity Employer. Candidates are evaluated without regard to age, race, color, religion, sex, disability, national origin, sexual orientation, veteran status, or any other characteristic protected by federal or state law..  . Anyscale Inc. is an E-Verify company and you may review the . Notice of E-Verify Participation.  and the . Right to Work posters in English and Spanish