---
title: "Group Lead Edge AI (human)"
company: "Neura Robotics"
company_url: "https://www.remjobs.works/companies/neura-robotics"
url: "https://www.remjobs.works/job/neura-robotics-group-lead-edge-ai-human-4f84a989-e243-458c-8943-d9937cac5e70"
apply_url: "https://jobs.ashbyhq.com/neura-robotics-gmbh/77b7aae9-bb90-457d-93a7-282e10295482"
workplace: onsite
location: "Metzingen / Riederich"
employment_type: full-time
seniority: lead
role: ai-machine-learning
region: other
skills: ["cpp", "linux", "python", "pytorch"]
date_posted: 2026-09-21T14:31:39.983Z
first_seen_by_remjobs: 2026-09-21T14:41:11.847Z
---

# Group Lead Edge AI (human)

**Neura Robotics** · Metzingen / Riederich

Apply: https://jobs.ashbyhq.com/neura-robotics-gmbh/77b7aae9-bb90-457d-93a7-282e10295482

## About Neura Robotics

Cognitive Robotics for Real-World Applications: NEURA Robotics enables safe and smart robot integration for Industry, Work and Everyday Life

## About the role

**Your Mission & Challenges**

As Group Lead Edge AI, you own the team that turns cutting-edge models into production-grade, on-device intelligence. You set the technical direction, make the hard calls on hardware and architecture, and stay hands-on enough to dive into a profiler when things get tough.

- Own the roadmap: Drive on-device AI from research to shipped product.

- Build and lead the team: Hire, mentor, and grow a team of edge AI engineers into the best in the field.

- Deploy at the edge: Take models from trained to deployed using quantization, pruning, distillation, and every trick it takes to make them fast and lean on embedded accelerator platforms (e.g. NVIDIA Jetson, Qualcomm IQ-series).

- Own the toolchain end to end: Cover model export and inference optimization frameworks (e.g. ONNX, TensorRT, AIMET) and the SDKs that turn a model into a working robot behavior.

- Partner across functions: Work with Hardware, Software, and Product to push the limits of what fits in the latency, power, and memory budget you're given.

- Set the bar for quality: Own benchmarking, on-device evaluation, and performance regression testing across every hardware target we ship.

- Get hands-on when it counts: Debug an accuracy drop after quantization, chase down a latency spike, solve the problem nobody else can.**What We Can Look Forward To**

- Strong academic foundation: An excellent Master's or PhD in Computer Science, Electrical Engineering, Embedded Systems, or a related field.

- Proven experience: 7+ years in ML or embedded AI engineering, with 2+ years leading technically. Real production deployment on embedded accelerators, not just papers.

- Hardware fluency: Hands-on experience with embedded AI hardware platforms (e.g. NVIDIA Jetson, Qualcomm IQ-series, or comparable).

- Optimization mastery: Deep expertise in model optimization from the model side to the metal: quantization, pruning, distillation, and architecture search.

- Toolchain expertise: Fluency with common model optimization and deployment toolchains (e.g. ONNX, TensorRT, AIMET, or equivalent vendor SDKs).

- Technical depth: Strong Python and C++, PyTorch experience, and comfort with embedded Linux and low-level profiling.

- The right mindset: A conviction that the only real test is the target chip, not the training cluster.

- Leadership & communication: The ability to lead engineers, make calls under uncertainty, and speak fluently to researchers, hardware engineers, and product alike. Professional English required; German a strong plus (B2 to C1).

---

Source: Neura Robotics's own career page, read by RemJobs. Canonical HTML version: https://www.remjobs.works/job/neura-robotics-group-lead-edge-ai-human-4f84a989-e243-458c-8943-d9937cac5e70