Location: Remote / EU

Stage: Early-stage startup

Product: Robotics automation platform

About the role

We are looking for a Lead Machine Learning Engineer (Robotics & Computer Vision) to join the founding technical team of a startup building a cutting-edge automation platform. Working closely with the CTO & Co-founder, you will own the product's ML core and shape its technical direction as the company scales.

To be clear: This is a highly hands-on role, not a corporate, LLM-wrapper, or prompt-engineering position.

We are looking for an ML/Deep Learning practitioner with a strong mathematical background who writes custom training loops, designs architectures (PyTorch/TensorFlow), and optimizes models for edge inference. As a primary builder from day one, your mission is to train deep learning models from scratch, develop robust computer vision pipelines, and integrate these capabilities into a commercially viable, physical robotics product within a high-performing engineering culture.

Your responsibilities

• Owning the AI/ML core of the product, working closely with the CTO & Co-founder to align it with the overall technical strategy,

• Writing custom training loops, designing and implementing neural network architectures (e.g., in PyTorch), and managing the end-to-end lifecycle from raw data processing to edge deployment,

• Building the AI/ML components of the MVP (managing the end-to-end AI/ML model lifecycle, from architecture design to training and fine-tuning and - where relevant - hardware control interfaces),

• Proposing and helping define the AI/ML stack and model architecture,

• Monitoring AI, computer vision, and robotics trends to maintain a competitive technological edge,

• Working closely with the CTO and, as the team grows, mentoring engineers joining the AI/ML function,

• Translating customer feedback and market needs into robust AI/ML technical requirements,

• Contributing to an internal culture focused on code quality, ownership, rapid iteration, and high execution standards.

Who we are looking for (must-have)

• 3+ years of end-to-end Deep Learning experience: From data processing and architecture design to training models from scratch and deep fine-tuning (no API prompting).