Mid-Senior Computer Vision Engineer (gn) @ AI Robotics Venture, Frankfurt a. M.
- On-site
- Frankfurt am Main, Germany
Job description
At Telekinesis, we're on a mission to revolutionize robotics by making robots an integral part of everyday life worldwide. We envision a near future where robots are as common as smartphones, seamlessly integrating into factories, offices, and—most importantly—homes.
To bring this vision to life, we're building a category-leading cloud platform that enables intuitive programming for all types of robots—industrial, mobile, drones, and humanoids. Powered by novel AI technologies, our platform allows robots to autonomously learn from human data, becoming more intelligent and adaptive with every interaction. Starting in the automotive industry, we're empowering factory workers to deploy industrial robots without prior expertise through our no-code platform.
At our core, we're driven by relentless innovation, tackling challenges others deem impossible and pushing the boundaries of what's possible in robotics. We're passionate, resilient, and unafraid of the hard work it takes to turn bold ideas into reality. This journey isn't for the faint of heart, but if you share our vision and thrive on breaking barriers, you belong here.
We're building a world-class team of roboticists, computer vision experts, and sales leaders, all driven by a shared passion for shaping the future of robotics. We are seeking an entrepreneurial Mid-Senior Computer Vision Engineer to join our team to develop the core classical computer vision and Deep Learning software stack.
The successful candidate will be responsible for:
Implementing diverse classical computer vision pipelines for tasks such as classification, segmentation, pose estimation, pose tracking, and anomaly detection.
Developing novel Deep Learning Networks, focused primarily on Convolutional Neural Networks and Transformer Networks, for segmentation and pose estimation.
Integrating the computer vision stack with the frontend to empower non-expert users to use these algorithms.
Testing the computer vision algorithms on industrial robots for industrial applications.
Leading junior computer vision engineers to implement different components of the algorithms and software stack.
Position details
Full-time position on-site at our Frankfurt, Germany, headquarters.
Desired skills
The candidate needs to meet the following basic qualifications:
M.Sc. in Computer Science (or a similar field) with research experience in Computer Vision.
2+ years of industrial experience in Computer Vision
Hands on experience working with point clouds and 6D pose estimation
Domain knowledge of advanced computer vision topics including: image segmentation, camera calibration, feature extraction, deep learning-based vision models, and (preferred) visual SLAM (Simultaneous Localization and Mapping).
Expertise with Python, OpenCV, Open3D/PCL, and PyTorch.
These additional robotics qualifications will be helpful:
Experience working with real robots, particularly industrial robots such as Franka Emika, ABB, KUKA, Fanuc, Denso, etc.
Fluent in English
What we offer
A pivotal role in defining the vision of our AI-based robotics cloud software, working directly with the CEO and CTO.
The unique opportunity to be among the first 10 engineers at a fast-growing startup, with the freedom to build a category-defining product in AI from the ground up.
A highly flexible and creative environment that encourages innovation and empowers you to bring your ideas to life.
A vibrant office space located in central Frankfurt, with flexible working hours to support work-life balance.
A dynamic, startup culture with a diverse international team, all driven by a shared passion for becoming global leaders in AI, robotics, computer vision, and software engineering.
- Frankfurt am Main, Hessen, Germany
or
All done!
We’ve received your application and look forward to reviewing it. In the meantime, please feel free to sign up for the Atlantic Labs & FoodLabs Talent Labs where you can easily browse & be recommended to relevant future opportunities.