Opportunity at
NebiusForward Deployed Engineer, Physical AI Infrastructure
Nebius, a Nasdaq-listed cloud infrastructure provider headquartered in Amsterdam with a global R&D footprint, is hiring a Forward Deployed Engineer for its Physical AI Infrastructure group.…
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About This Role
Nebius, a Nasdaq-listed cloud infrastructure provider headquartered in Amsterdam with a global R&D footprint, is hiring a Forward Deployed Engineer for its Physical AI Infrastructure group. The company develops a full-stack AI cloud platform designed to assist enterprises and developers with model training, data management, and production deployment. This on-site role places you within the Physical AI go-to-market team, where you will collaborate directly with customers, NVIDIA, Product, and Engineering.…
Job Description
Nebius, a Nasdaq-listed cloud infrastructure provider headquartered in Amsterdam with a global R&D footprint, is hiring a Forward Deployed Engineer for its Physical AI Infrastructure group. The company develops a full-stack AI cloud platform designed to assist enterprises and developers with model training, data management, and production deployment. This on-site role places you within the Physical AI go-to-market team, where you will collaborate directly with customers, NVIDIA, Product, and Engineering.
In this capacity, you will support enterprises, independent software vendors, and digital-native organizations running evaluation, model serving, synthetic data, simulation, and training workloads. You will assist customer engineers with system setups, benchmark open-weight models using serving stacks like vLLM or SGLang, develop specialized agents, and troubleshoot issues spanning Python, Kubernetes, GPUs, and networking. Additionally, you will gather evidence from customer implementations to shape core infrastructure products, assess new product opportunities, build prototypes, and run technical evaluations.
This position suits an experienced technologist with a background in software engineering, DevOps, or cloud infrastructure who enjoys hands-on problem-solving and direct customer engagement. The ideal candidate can translate complex, unfamiliar user requirements into concrete infrastructure needs while navigating enterprise security and operational standards.
Responsibilities
- Collaborate with client engineers to analyze infrastructure constraints, production needs, and workload characteristics.
- Convert Physical AI use cases into actionable requirements for Serverless, Cloud, and Token Factory teams using data and customer evidence.
- Pinpoint enterprise adoption hurdles and shared industrial requirements, partnering with Product and Engineering to evaluate gaps and test solutions.
- Develop agents to establish, execute, and debug Physical AI workloads across clusters, model servers, storage, and schedulers.
- Deploy, tune, and benchmark open-weight models utilizing serving stacks such as SGLang or vLLM.
- Create prototypes and perform technical assessments to verify performance, reliability, and product suitability.
- Examine market demand and alternatives for initiatives outside current product scopes, building solutions where clear markets exist.
- Troubleshoot issues across Python code, agents, model servers, Kubernetes, storage, networking, and GPUs.
- Convert successful deployment configurations into short guides, reusable scripts, and repeatable setups.
Requirements
- Minimum of three years of professional experience in software engineering, cloud infrastructure, DevOps, or machine learning infrastructure, including the ownership of a platform, cluster, or production service.
- Demonstrated experience interacting directly with external engineers or clients to scope problems, explain technical trade-offs, and execute evaluations.
- Capability to convert unfamiliar user issues into precise infrastructure specifications.
- Practical background building with language models or agents, either professionally or independently, with comprehension of their internals like transformers, tool calling, or KV caching and output evaluation.
- Familiarity with enterprise infrastructure demands, covering network isolation, identity and access management, security, monitoring, and reliability.
- Advanced Python and Linux competencies, including reading unfamiliar scripts, automating environments, and debugging via metrics and logs.
- Hands-on expertise with containers and Kubernetes, encompassing scheduling, networking, configuration, and storage.
- Track record of delivering functional software under incomplete requirements, evaluating outcomes, and collaborating with end users.
Qualifications
- Background in enterprise customer engineering, consulting, solutions architecture, or guiding a new product from an initial client problem to full adoption.
- Familiarity with distributed compute frameworks such as Ray, Spark, Slurm, or multi-GPU tasks.
- Experience with NVIDIA GPU workloads, including CUDA, NCCL, memory management, drivers, and monitoring.
- Proficiency with model serving frameworks such as TGI, vLLM, TensorRT-LLM, or SGLang.
- Exposure to robotics, reinforcement learning, simulation, world models, synthetic data, or specialized tooling like Cosmos, Omniverse, Isaac Lab, and Isaac Sim.
- Knowledge of infrastructure automation and enterprise integrations, including CI/CD, Terraform, identity federation, and private connectivity.
Core Skills
Benefits
- Competitive compensation package
- Opportunities for professional career growth and learning
- Flexibility and ownership in your work
- Collaborative and innovative working culture
- Engagement with impactful artificial intelligence projects
- International environment featuring talented teams
Frequently Asked Questions
Answers are based only on the employer’s listing; where it doesn’t say, neither do we.
What is the location and remote policy for this role?
The posting specifies that the role is on-site, though a specific city or country location is not stated in the source text.
What type of employment is this position?
This is a full-time position.
What qualifications are required for the Forward Deployed Engineer role?
Candidates must have three or more years of experience in software engineering, DevOps, cloud infrastructure, or ML infrastructure, along with strong Python and Linux skills, experience with containers and Kubernetes, and a background in working directly with customers to scope problems.
What salary does Nebius offer for this position?
The salary is not stated in the job posting, though the company offers competitive compensation.
Are there specific eligibility requirements to apply?
Applicants must be authorized to work in the country where they apply and will need to supply proof of employment eligibility upon hire.
Sample Interview Questions
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