The role
As an AI Engineer for RL Post-Training and Agentic Systems, you enter as a key member of the early AI team. You will work directly with our AI leadership and researchers to define the infrastructure we use to post-train our robot foundation models with large-scale reinforcement learning and deploy them as agentic systems across our robot fleet. You own the full loop - from distributed rollouts in simulation and on real robots, through policy optimization, to serving our models on cloud and on-prem infrastructure. The systems you build close the gap between research and deployment, turning real-world experience into better models, fast and safely. This is a full-time, permanent position.
AI Engineer - RL Post-Training and Agentic Systems
Munich, Limassol
Full-time
Permanent employee
Your mission
Your profile
Key responsibilities
We seek people who embrace the empirical nature of AI research and want to accelerate our research velocity with best-in-class tools - so that we can all make breakthroughs faster, together.
- Distributed RL Infrastructure: Develop scalable infrastructure for RL post-training of multi-billion-parameter robot foundation models, coordinating distributed actors, learners and reward models across GPU clusters, simulation and our robot fleet
- Model Serving: Own our cloud and on-prem serving infrastructure, delivering low-latency, high-throughput inference for both RL rollouts and production robots, including fast weight synchronization between training and inference.
- Agentic Workflows: Build the infrastructure to orchestrate, evaluate and monitor agentic systems that combine our models with planning, tool use and robot skills to complete long-horizon tasks.
We seek people who embrace the empirical nature of AI research and want to accelerate our research velocity with best-in-class tools - so that we can all make breakthroughs faster, together.
- Experience: 3+ years of hands-on experience building and operating large-scale RL or post-training systems for large models, including actor-learner architectures, asynchronous rollouts and off-policy correction.
- Core Skills: Deep expertise in RL post-training and high-performance model serving. In detail:
- RL Post-Training: PPO, GRPO and related policy-optimization algorithms, reward modeling, and frameworks such as veRL, OpenRLHF, NeMo-RL, TRL or Ray RLlib.
- Model Serving: Inference engines such as vLLM, SGLang or TensorRT-LLM, batching and KV-cache optimization, quantization, and serving platforms such as Ray Serve, Triton Inference Server or KServe.
- Distributed Systems: Ray, Kubernetes and/or Slurm, fault-tolerant orchestration of heterogeneous workloads, and monitoring with Prometheus and Grafana.
- Core Stack: Python, PyTorch and/or JAX, CUDA, NCCL, and distributed training with FSDP or Megatron-Core.
- A plus: Building agentic systems and evaluation harnesses for long-horizon, multi-step tasks; robot learning in simulation and sim-to-real transfer (Isaac Sim/Isaac Lab, MuJoCo, domain randomization); edge and on-robot inference (NVIDIA Jetson/Orin/Thor, TensorRT, ONNX Runtime) under real-time latency constraints; robotics middleware and data formats (ROS 2, MCAP)
- Mindset: You balance the agility of a startup with the professional rigor required for a global industrial player. You are a curious builder who thrives in a collaborative, fast-paced research environment, and an engineer with a research mindset who understands the workflows of cutting-edge AI research and supports them with rigorous software engineering.
Why us?
- The Team: Work alongside leadership with a proven track record of building unicorn-scale companies and defining global robotics standards.
- Smart Strategy: We operate as disciplined fast followers. Capital is timed to the deployment inflection point, avoiding early-mover dead ends to scale fast on proven foundations.
- Resources: We are substantially internally funded and attract top-tier investors to avoid any capital constraints for our mission.
- Historic Opportunity: Join at the dawn of a new industry comparable to the rise of the automobile. Help shape the European champion in this trillion-dollar market.
About us
We are building a global leader in physical AI, anchored in Europe’s strongest robotics heritage. Founded by entrepreneurs with backgrounds in scaling digital products and advanced robotics, the team is bolstered by senior leadership from top-tier AI research labs and industrial tech companies.
Driven by a mission to create versatile and trustworthy embodied AI for physical labor, we fuse deep engineering mastery in AI and mechatronics with a rapid-execution culture. We are addressing the labor shortage by closing the gap to production-grade deployment. This means building the trusted alternative: robots that are safe, secure, and engineered to automotive standards of scale and durability.
We are well-capitalized and now assembling our team.
Our Locations: Vesoma has two main locations: Munich, Germany and Limassol, Cyprus. This pan-European setup represents our core ambition of building a European technology leader, gives us a great talent base and a strong corporate structure.
We are an equal opportunity employer.