Senior Machine Learning Engineer (Robotics & Computer Vision)

Location: Remote / PL Stage: Early-stage startup Product: Robotics automation solutions About the role We are looking for a Senior Machine Learning Engineer (Robotics & Computer Vision) to join the technical team of a startup building cutting-edge automation solutions. 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/Vision 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/Vision 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/Vision 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). Proven track record of engineering advanced Computer Vision systems within the industrial automation sector. 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, Prior leadership experience (Lead Engineer, Tech Lead) is a plus, though not required.

What we offer Key technical role 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 Tech Interview (~ 60 min.) Technical assignment Discussion of the technical task Interview with the Investor (~45 min) Agreeing on the terms of cooperation (remuneration)