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Machine learning engineer - computer vision (m/f/d)

München
eGym GmbH
Ingenieur
Inserat online seit: 28 Oktober
Beschreibung

Your daily workout Join our ambitious team in Munich pioneering technology at the intersection of Fitness, Health Tech, Computer Vision, and Machine Learning! We are researching and developing prototypes for early‑stage breakthrough product initiatives. We need a self‑starter who thrives in a rapidly evolving environment, appreciates high autonomy, and is ready to make a significant impact. You bring to the table proven expertise in deep learning, ideally paired with robust data pipelines, 3D perception, human motion, or real‑time inference at the edge. Ready to shape the future of fitness technology? Apply now! Machine Learning: You build ML models for Computer Vision tasks - define experiments, perform data reviews, and iteratively improve model performance Prototyping: You get your hands dirty building prototypes and support the team with user experience testing and other necessary tasks Ownership: You are fearless in taking decisions, asking questions, proposing solutions, experimenting, and failing fast Communication: You effectively communicate progress, challenges, and solutions with the rest of the team Architecting: You experiment with and architect solutions iteratively Your fitness level Core Experience: You have proven experience (2+ years) building and orchestrating ML models for Computer Vision tasks Technical Stack: You are highly proficient in Python and expert in relevant ML frameworks (PyTorch, TensorFlow/Keras) and packages (NumPy, Pandas) Data Skills: Preferably, you have hands‑on experience with data science tooling and expertise in dataset curation, analysis, and cleaning for ML training Code Quality: You write high‑quality, maintainable code using sound software engineering principles and are familiar with CI/CD tools Foundations: You have a solid theoretical and practical foundation in the fundamentals of ML, Computer Vision and follow the latest trends in related applications (e.g. human pose estimation, multi‑view geometry, active learning, or semi‑supervised labeling) Your training goal for your first 6 months Integration: You integrate into our team and deeply understand the current product context and vision Familiarity: You master the relevant theoretical concepts and cutting‑edge tech stack, including Edge AI, ROS2/gstreamer, Docker containers, and real‑time inference Pipeline: You drive the design and implementation of novel Computer Vision pipeline components to address real‑world problems where no "off‑the‑shelf" solutions exist Validation: You take part in validating your solutions and gathering feedback through dedicated user experience tests The equipment we provide Best‑in‑class Development Tools: Assess AI tools for designing, coming up with solutions, and coding Impact & Ownership: Shape the product itself, ensuring your work in our fast‑learning environment has real‑world impact from day one Modern Culture: Be part of a modern and international company culture where talent and passion are welcomed, heard, and part of the decision‑making process Work‑Life‑Balance: Benefit from flexible working hours, hybrid working policy (2 office days), and 30 days of vacation per year Fit & Healthy: Train for free with EGYM Wellpass in several thousand sports and health facilities across Germany and/or use our in‑house gym with EGYM products Mentoring Program: Exchange knowledge and grow together across teams and locations through our self‑organized mentoring platform Mobility: Enjoy a monthly travel subsidy for public transport Discounts: Get a variety of great discounted offers, from fashion to leisure, through our employee benefits portal Bike Leasing: Stay active and use our leasing bike offer on your way to work or in your spare time Subsidized Pension: Profit from our employer‑subsidized pension Your warm up plan Contact Information Upload your documents (CV, salary expectations and earliest possible start date) and specify the job ID #1765. Contact: Marina Lambrecht For further information: Website #J-18808-Ljbffr

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