# Forward Deployed Robotics Engineer

**Company:** [Black Forest Labs](https://hotfix.jobs/companies/black-forest-labs)
**Location:** Freiburg, Germany
**Role:** Solutions Architecture
**Salary:** €120k – €180k/yr
**Skills:** Robotics, Generative AI, Action Models, Vla Models, Π0, Lerobot, Imitation Learning, Reinforcement Learning, Policy Learning, Diffusion Models, Flow Matching, Transformer Models, Backend Engineering, Frontend Development, Cloud Platforms
**Posted:** 2026-06-29

> Embeds with robotics and physical-AI customers to deploy, fine-tune, and productionize BFL models on real robots. The role combines customer-facing solution delivery with robotics, model serving, backend/frontend engineering, and research prototyping.

## Job Description

## Responsibilities
- Partner with customers to design and ship integrations, fine-tunes, and interfaces on top of BFL’s models, including action/VLA models, from first prototype to production.
- Deploy models in customer environments with strong latency and output quality on real robots, across on-premises and BFL-hosted deployments, including real-time and edge constraints.
- Identify high-value customer use cases and prototype solutions quickly.
- Identify and own opportunities to expand BFL technologies into new domains.
- Prototype techniques from recent research papers in collaboration with the research team.

## Requirements
- Proven track record as a robotics engineer, forward deployed engineer, or technical founder.
- Experience working directly with customers, iterating on solutions, and providing tailored support for serving generative AI models.
- Hands-on experience with action/VLA models and the surrounding open ecosystem, including π0/π0.5 and LeRobot.
- Experience with imitation learning, reinforcement learning, or policy learning.
- Ability to work across model hosting, backend engineering, frontend development, and UI construction.
- Excellent communication skills and experience collaborating with technical and non-technical stakeholders.
- Ability to explain complex technical concepts clearly to technical and non-technical audiences.

## Nice-to-haves
- Knowledge of diffusion models, flow matching, fine-tuning, and distillation techniques.
- Experience optimizing inference for transformer-based machine-learning models.
- Ability to architect solutions in complex enterprise environments.
- Contributions to open-source projects in diffusion models, robotics, or simulation.
- Experience with cloud platforms and modern deployment solutions.

## Compensation
- Base annual salary: **€120,000–€180,000**, plus equity.

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