Research Engineer
About the job
- Deep experience and understanding at the intersection of machine learning, systems engineering, and robotics.
- Experience training, fine-tuning, and deploying modern deep learning architectures, including Transformers, vision-language models, vision-language-action models, imitation learning, and reinforcement learning, for robot control; policies validated on real hardware are ideal.
- Strong software engineering and infrastructure skills, with proficiency in Python and deep learning frameworks such as PyTorch or JAX, and the ability to write clean, scalable code for training and evaluation.
- Comfort working hands-on with hardware and understanding of the robotics full stack, including perception, controls, and state estimation, and how to debug failures when software meets the physical world.
- Ability to move between research and implementation, prioritizing execution, iteration speed, and real-world robustness over theoretical purity.
- Design, implement, and maintain the core infrastructure for large-scale vision-language-action model training, including scheduling, distribution, job management, checkpointing, and rigorous logging.
- Build tools and abstractions for launching, monitoring, debugging, and reproducing complex, multi-variant experiments.
- Use offline data from classical robotic stacks to pre-train robust robot foundation models.
- Translate core research needs into infrastructure capabilities, track experiments, analyze results, and coordinate with machine learning researchers to support model progress.
- Design robotic tasks and lightweight physical setups to evaluate model capabilities beyond simulation.
- Configure and calibrate robots for rollouts, coordinate data collection, and run structured on-robot evaluations to measure real-world success rates.
- Analyze real-world evaluation results to guide machine learning research, identify operational bottlenecks across software, hardware, and deployment systems, and improve iteration speed.
- Beta test internal and third-party tools for teaching robots new skills, and write structured documentation so the broader team can reproduce workflows and scale their impact.
About the company
Nomagic builds intelligent robotics solutions for e-commerce logistics to automate warehouse tasks and reduce human work. Its products combine hardware robots with software that use artificial intelligence and machine learning to handle repetitive activities in warehouses, including inventory management and order fulfillment, and to integrate with existing warehouse systems. The company generates revenue from selling robotic systems and providing ongoing service contracts for maintenance and software updates. Distinguished by offering a tightly integrated hardware-and-software platform that can slot into current warehouse operations, Nomagic aims to keep warehouses running smoothly and without interruptions. Its goal is to transform warehouses into fully automated environments capable of meeting the high throughput needs of modern e-commerce.
Company Size
201-500
Company Stage
Series B
Total Funding
$93.4M
Headquarters
Warsaw, Poland
Founded
2017
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Simplify's Take
What believers are saying
- Zalando is scaling to 50 robots after a 100,000-pick daily pilot.
- Nomagic raised $10 million in January 2026 and $44 million in February 2025.
- Brack expanded VLA deployment in May 2026, validating autonomous night-and-weekend operations.
What critics are saying
- Zalando and Brack dominate revenue concentration, creating renewal risk by 2027.
- Competitors like Covariant and Locus Robotics attack the same warehouse automation buyers.
- A reliability slip in live warehouses would block deployments and kill Nomagic's hardware sales.
What makes Nomagic unique
- Nomagic runs live warehouse VLAs with Brack.Alltron and Zalando in 2026.
- Its Library of Chaos uses millions of real picks from 24/7 operations.
- Markus Wulfmeier, ex-Google DeepMind, now leads robotics foundation models at Nomagic.
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Benefits
- Health Insurance
- 401(k) Retirement Plan
- Remote Work Options
- Flexible Work Hours
- Paid Vacation
- Paid Holidays
- Sabbatical Leave
- Hybrid Work Options
- Stock Options
- 401(k) Company Match
- Performance Bonus
- Profit Sharing