(Senior) Machine Learning Engineer, Robot Learning (m/f/d)
Batch Robotics is revolutionizing how robots operate in factories — not through rigid programming or teaching by human demonstration, but wi
Batch Robotics is revolutionizing how robots operate in factories — not through rigid programming or teaching by human demonstration, but wi
Entwicklung moderner Backend- und Datenplattformen auf Basis von Java, Boot.
is mostly focused on shipping AI product features, with some AI systems and infrastructure work where needed.
At Machine Learning Architects Basel (MLAB), we assist and empower people and organizations in designing, building, and operating reliable d
AI & Data Science Consultant Du hast Lust, AI & Data Strategien und Use Cases zu entwickeln und umzusetzen, Geschäftsprozesse durch KI-basie
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Konzipiert AIoT-Architekturen (Hardware, Connectivity, Cloud) für Industriekunden, definiert GenAI- und AI-Ops-Services und führt ein Entwicklerteam fachlich.
Umsetzung von individuellen Applikationen in interessanten und herausfordernden Kundenprojekten auf Basis von ASP.NET Code (Razor/Blazor) un
KI-Features liefern, die Zahlen bewegen: Du verantwortest KI-Features end-to-end – Belegerkennung, Klassifizierung, automatisches Verfassen
Our client is a leading supplier of software products in the field of eCustoms internationally.
Analysiert Logistikprozesse, setzt Digital Twins und ML-Lösungen beim Kunden um, leitet Projekte und integriert sie in SAP.
Verwaltungssprung is a Berlin-based GovTech company developing AI-powered software solutions to simplify and digitize administrative processes.
Deine Leidenschaft für die Frontend- und Backend Entwicklung kannst du in unseren spannenden und innovativen Projekten im AIoT (AI und IoT)
is mostly focused on shipping AI product features, with some AI systems and infrastructure work where needed.
is mostly focused on shipping AI product features, with some AI systems and infrastructure work where needed.
Als AI Engineer (w/d/m) schreibst du nicht nur Notebooks und Prompts, du baust produktive GenAI-Systeme: Agenten, RAG-Pipelines, LLM-getrieb
Baut No-Code-Automationen mit n8n, Make und Zapier, entwickelt KI-Agenten, pflegt Airtable-Datenbanken und betreut Kunden technisch.
Anspruchsvolle Projekte mit LLMs, Agentic RAG und AI-Agent-Frameworks wie LangGraph oder OpenAI Agent SDK.
is mostly focused on shipping AI product features, with some AI systems and infrastructure work where needed.
Entwicklung und Umsetzung einer unternehmensweiten KI-Strategie in direkter Berichtslinie zur Eigentümer - Geschäftsführung | Identifikation
As our first Senior Data Scientist, you’ll be a core part of building the intelligence behind Skalar.
Du entwickelst und steuerst unseren gesamten Recruiting-Prozess für vorwiegend technische Rollen, einschließlich der Identifikation und akti
Du entwickelst Software mit Angular, Spring Boot, Kubernetes – für klassische und AI-basierte Lösungen Du gestaltest mit unseren Kunden ansp
Batch Robotics is revolutionizing how robots operate in factories — not through rigid programming or teaching by human demonstration, but wi
Du leitest AI- und Machine-Learning-Projekte bei unseren Kunden Du übersetzt Business-Anforderungen in pragmatische technische Lösungen Du v
Baut KI-gestützte Workflows und Automationen mit Make und Airtable, testet neue KI-Tools und erstellt Social-Media- und Content-Prozesse.
Warum dieser Job gelistet ist
Eindeutige KI-Rollenbezeichnung im Stellentitel. Prüfverfahren ansehen
Background (must-have): Either (a) a Master s degree in Robotics, Computer Science or a related field plus at least 3 years of full-time professional experience after graduation – internships, working-student jobs and thesis projects do not count towards these 3 years – or (b) a PhD in one of these fields that is completed or will be completed within the next 4 months. Availability (must-have): You can start full-time in Munich (hybrid) within a maximum of 4 months. Deep experience: Hands-on work with reinforcement learning (RL) and imitation learning within physics simulations.
Software Engineering: Strong proficiency in Python and ideally Rust; ability to write clean, modular, and performance-optimized code for distributed workloads using AI agents. Real-World Mindset: Proven track record of deploying models on physical robotic manipulators and handling noisy, temporal, or large-scale datasets. Soft Skills: Entrepreneurial drive, solution-oriented mindset, high agency and the ability to take direct responsibility in a fast-paced startup environment.
Impact: The unique opportunity to rethink industrial automation for batch-size-1 with cutting-edge AI to maintain European manufacturing sovereignty. Growth: Challenging tasks and impactful projects alongside experts in a high-growth VC-funded startup. Ownership: opportunity to actively shape the company s technical direction; potential shares in the company.
Environment: A modern, central workspace in Munich with a collaborative, international culture. Please note: We can only consider applications that meet the must-have criteria above – i.e. at least 3 years of full-time professional experience after your Master s (internships and working-student positions excluded) or a PhD completed within the next 4 months, and availability to start within 4 months. Please state your earliest start date (and, if applicable, your expected PhD completion date) in your application.
Want to shape the future of industrial robotics? We look forward to meeting you!
Batch Robotics is revolutionizing how robots operate in factories — not through rigid programming or teaching by human demonstration, but with smart perception and AI intelligence. We are a team of 8 motivated people with 50 years of experience in industry and robotics. Our mission is to make robots smarter and more flexible, enabling batch-size-1 automation for surface treatment economically.
Our technology helps factories in Europe to remain competitive with intelligent robotics. We are now looking for a Senior Machine Learning Engineer with at least 3 years of full-time industry experience (or a PhD finishing within 4 months), technical excellence and entrepreneurial drive to join us in developing the next generation of AI-driven robotic systems! Tasks End-to-End ML Systems: Design, implement, and train state-of-the-art AI models for perception and control of robot arms.
Data Pipelines & ML Ops: Collect real-world data from factory deployments to optimize model training and update models in the field. Simulation & Synthetic Data: Work and improve simulation-based tooling (e.g., NVIDIA Newton Physics Engine) for physical AI and scalable synthetic data generation. Model Development: Build ML components across perception and policy pathways, including video models, multimodal encoders, world models, and diffusion/transformer architectures.
Systems Integration: Work with real-world, multimodal datasets (vision, force/torque, tactile) and ensure models operate reliably under real-time constraints on physical hardware. Evaluation & Iteration: Test models in realistic environments, analyze failures, and refine for stability, latency, and robustness.
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