The Role (anywhere from EUROPE, remote)

The role

As a Senior ML/AI Engineer, you'll lead the vision and technical development of our cutting-edge smart industrial environment recognition platform. This role presents an exciting challenge where you'll leverage zero-shot and one-shot object detection, along with advanced semantic segmentation techniques. You'll conduct sophisticated experiments to drive meaningful outcomes through unsupervised analysis of video, audio, and text data. Your work will push the boundaries of what's possible in industrial recognition, making a significant impact on the future of smart environments.

What You'll Do

• Lead the development of our cutting-edge smart industrial environment recognition platform.
• Enhance and integrate early-stage data collection, data generation, and auto-annotation algorithms.
• Optimise LLM Agents for efficient and accurate information retrieval flows.
• Build and scale adaptive data curation pipelines.
• Innovate by finding data and time-efficient methods to train advanced deep learning models, leveraging Sim2Real and Real2Sim techniques with both synthetic and real data.
• Apply state-of-the-art methods to advance the next generation of robotics, collaborating with a multidisciplinary international team.

Who you are

• A highly skilled and experienced ML/AI engineer with a strong background in computer vision, natural language processing, audio processing, classical machine learning, and deep learning.
• A professional software engineer with over 5 years of experience in implementing solutions for production-grade systems.
• Proficient in Python with familiarity in other programming languages, such as C++.
• Experienced with deep learning frameworks like PyTorch and TensorFlow, and computer vision tools such as OpenCV, NumPy, and Pandas.
• Possesses deep knowledge in model optimisation, conversion, and deployment, with experience in edge device computing.
• Hands-on experience with zero-shot, one-shot, or few-shot recognition algorithms.
• Skilled in unsupervised clustering and analysis algorithms.
• Experienced in MLOps, including experiment tracking, data versioning, and model serving on platforms like MLFlow, W&B, CometML, ClearML, etc.
• Product-oriented with a strong ability to deconstruct complex problems into manageable sub-problems and develop efficient, hierarchical solutions.
• Capable of working effectively within multidisciplinary and international teams, with excellent communication skills to articulate complex architecture and solution designs clearly and compellingly.
• Passionate about robotics, automation, and the transformative potential of intelligent systems.

Nice to Have

• Experience with ROS, Docker, Kubernetes, AWS / GCE.
• Experience with NVIDIA edge devices, deployment and robotics stack.
• Experience with Gaussian Splats and NeRFs.
• Experience with Multi Domain models and contrastive learning.
• Experience with 3D software such as Unity3D, Omniverse and Godot.