Machine Learning Engineer

Job description

Machine Learning Engineer

Permanent; Remote

About us:

Be part of an exciting, well-funded startup changing the world of retail. RADAR's mission is to revolutionize customer experience in retail through precise identification of inventory in the stores and distribution centers, completely transforming the in-store experience for employees and customers alike. RADAR's proprietary hardware and software platform combines RFID, Computer Vision and AI to provide hyper-precise, real-time location of every product and person in physical stores. This unprecedented capability enables retailers to automate in-store inventory management, analytics, and checkout...and this is just the beginning of what we hope to accomplish together.

About the job:

We are looking for Machine Learning Engineers to help build the next generation of the RADAR platform. This role involves direct collaboration with the core research team to bring cutting edge machine learning and computer vision applications into production.


  • Work with the research team to productionize state-of-the-art machine learning and computer vision algorithms
  • Select, design and develop the tooling and infrastructure required to support the end-to-end ML lifecycle
  • Establish and extend best practices for MLOps at RADAR


  • Bachelor's degree in Computer Science or a relevant field
  • 4+ years of relevant industry experience in software engineering and/or machine learning
  • Strong proficiency with Python and C++, as well as relevant packages such as Pytorch and Tensorflow
  • Experience with the design, development and maintenance of highly performant and reliable backend systems
  • Experience with prototyping, benchmarking and productionization of end-to-end machine learning / deep learning applications
  • Exceptional communication and collaboration skills


  • Master's degree in Computer Science or a relevant field
  • Experience working with video streaming and encoding / decoding
  • Experience working with real-time distributed systems and/or edge computing
  • Experience with the setup and operation of computing clusters for modern deep learning workloads
  • Experience in deploying ML algorithms in resource-restricted environments such as embedded systems
  • Strong familiarity with modern MLOps tooling and workflows

What We're Looking For In Teammates

Technology like what we're building doesn't happen on its own. It is the result of a collaborative environment and the hard work of passionate, dedicated individuals working intelligently towards a common goal. We are looking for exceptional people to join our growing team and have a positive impact on our culture, technology, and product from day one. We deeply value humility, curiosity, and a positive attitude and you should as well. You should also believe that mutual respect is the foundation of any healthy and productive relationship. You should be unafraid to ask questions or challenge responses no matter how simple or complex. Most importantly, you should value honest and direct communication as you recognize that this is the best way for any individual or team to continuously learn and grow. Accomplishing our collective goals will be fun but it will also be hard; you should be in pursuit of an ongoing and rewarding challenge!

What It's Like To Work With Us

We're passionate about the technology we've created and what we're building, but we know that changing any industry and creating a successful company will take balance, maturity, and a sustained effort. We've combined retail industry expertise, amazing engineers with experience shipping real-world hardware and software solutions, and a team of brilliant minds who are not afraid to focus on solving impossible problems. But this passion doesn't mean we live unbalanced lives. We have families and passions outside of work, and we know that the best work comes from sharp, rested people. We respect each other and each of our contributions, and we believe that the best solutions will come from a diversity of ideas and perspectives.

Finally, we build our products with deep empathy for the people who will use them every day. Their input and insights are our clearest guide to building what they need; we respect our partners and clients, and listen closely to their feedback.

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