Machine Learning Manager

Job Description

Do you get excited when ML models interact with the physical world?

Are you ready to learn about the new, exciting world of smart robots?

Do you thrive in a fast-paced and dynamic (startup) environment?

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’re now looking for a Machine Learning Manager, who’s ready to deep dive into the hard problems of understanding the real world (trying to match with software the millions of years of development leading to the human hand + eye), guide and unblock multiple ML efforts, and collaborate closely with other parts of the organisation.

Offer essentials:

Play with robots every day

Salary: 34,000 - 45,000 gross UoP per month + equity

Relocation package if you are willing to move to Warsaw

English-speaking environment

Partly remote work is possible!

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

We are scaling our machine learning team significantly

We combine world-class research with top-notch engineering and apply it to solve real problems

We build robots powered by AI

We have them in production at scale and see their real impact on critical operations.

We are still pretty small, so everyone has a direct impact on the product and how we work

Our team has built Google Warsaw, unicorn startups (Climate Corp), tested rocket engines and worked at top companies such as Nvidia or ByteDance. Now we shape the future of smart robotics together!

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

Building self-organised, well-functioning teams, focused on making our robots intelligent and our customers happy

Building a culture of trust and open feedback, disregard for the impossible!

Enhancing 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

Preparing and executing research and development efforts and their production roll-outs

Developing interfaces and APIs for the integration of machine learning algorithms with robots and warehouse management systems