Nomagic

Machine Learning Manager

Nomagic  •  Warsaw, PL (Remote)  •  5 days ago
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Job Description

Do you get excited when your software actually interacts with the physical world?
Are you ready to learn the new, exciting world of smart robots?
Do you want to build an engineering organisation from its early days?
Do you feel tired of working in a big company?
Would you like to cooperate with top professionals in our industry?

If your answers are mostly yes, then you should keep reading.

At Nomagic, we’re on a mission to teach robots the real world. We are looking for a Machine Learning Manager who’s ready to deep dive into the hard problems of physical manipulation (trying to match with software the millions of years of development leading to the human hand + eye) and at the same time build a healthy team.

Offer essentials:

  • Play with robots every day
  • Salary: 42,000-48,000 gross UoP per month + equity
  • Relocation package if you are willing to move to Warsaw
  • No late evening calls - the entire team is based in Europe :)
  • English-speaking environment
  • Partly remote work is possible!

Here is why we love this job ourselves, and hope you will enjoy it too:

  • We combine world-class research with top-notch engineering and apply it to solve real problems
  • We build robots powered by AI
  • We already have them in production
  • We are still pretty small, so everyone has a direct impact on the product
  • Our team has built Google Warsaw, unicorn startups (Climate Corp), led research in DeepMind, tested rocket engines and worked at top companies such as Nvidia or ByteDance. Now we shape the future of Physical AI together!

Some of the problems you may try to solve with us:

  • Leading research and development efforts to enhance robots with capabilities to autonomously manipulate objects using advanced grippers (suction cups, finger grippers and other advanced tools)
  • Taking responsibility for deploying and continuously improving ML systems in production and measuring their impact in a data-driven way
  • Developing interfaces and APIs for the integration of machine learning algorithms with robots and warehouse management systems

What skills we’d like you to have:

  • 5+ years of experience with production-grade deep learning systems; computer vision is a strong plus
  • Technical leadership skills & experience
  • Great problem-solving and proficiency in one of the modern programming languages (we use Python and C++)
  • Fluent communication in English

What should you expect once you apply?

  • 30-minute call with a Recruiter
  • 60 minutes Technical prescreen
  • 45 minutes Hiring manager interview
  • Onsites - half a day of interviews & discussions at the office
  • Reference check

  • We make the final decision after max. 2-3 days after an onsite interview. Important: expect detailed feedback regardless of our decision.

Nomagic

About Nomagic

Nomagic delivers AI powered robotic picking solutions that transform how warehouses operate. Our advanced vision systems and machine learning algorithms enable robots to handle millions of different items with speed and precision, helping e-commerce, retail and logistics leaders achieve new levels of efficiency, accuracy and scalability.

From piece-picking automation to seamless integration with warehouse management systems (WMS), Nomagic’s technology is designed to reduce operational costs, solve labour shortages and meet ever growing customer expectations.

We work with leading brands and fulfilment providers worldwide to optimise their order fulfilment, returns processing and inventory management, all while delivering a faster, more reliable supply chain.

Specialties: AI robotics, warehouse automation, robotic picking, computer vision, machine learning, fulfilment optimisation, e-commerce logistics, retail supply chain solutions.

Mission: To make warehouses smarter, more flexible and more sustainable through cutting-edge robotics and AI.

Industry
Architecture & Engineering
Company Size
51-200 employees
Headquarters
Warsaw, PL
Year Founded
2017
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