Lead Machine Learning Engineer (Robotics & Computer Vision)

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).

Advanced framework proficiency: Deep understanding of modern DL tools (PyTorch preferred), including writing custom data loaders and loss functions.

Computer Vision expertise

Hands-on background with CNNs, ViTs, object detection, and segmentation.

Solid software engineering foundation: Proven track record of building and shipping ML components in real, production-ready products.

Startup mindset: Pragmatic, analytical, and comfortable in fast-paced, high-uncertainty environments where rapid execution beats over-engineered code.

Language skills

Fluent Polish and English (spoken and written).

Nice to have

Experience with hardware control/integration of AI models with physical systems (robotics, embedded systems, IoT),

Experience with robotics technologies (ROS/ROS2, simulation environments, control systems),

Experience in robotics automation platforms, cloud-edge architecture, or industrial automation,

Background in deep-tech, robotics, or engineering-driven startups,

Hands-on experience in computer vision,

Prior leadership experience (Lead Engineer, Tech Lead) is a plus, though not required.

What we offer

Key technical role in the founding team of a robotics startup, with real influence over the AI/ML direction of the product,

Opportunity to build the AI/ML core of a robotics startup from scratch,

Remuneration

at least PLN 18 000 net B2B + VAT,

Equity/incentive package as the company and role grow,

Support from an experienced startup studio and capital group,

Access to industry experts and startup-building know-how,

Fast decision-making and a high-impact environment.

Red Sky is conducting this recruitment process. The cooperation concerns a newly established start-up.

Recruitment process

Interview with HR (~45 min)

Tech Interview (~ 60 min.)

Interview with the CEO (~30 min)

Interview with the Investor (~45 min)

Workshops (technical & product alignment)

Agreeing on the terms of cooperation (remuneration )

Originally posted on Himalayas