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4 Jan 2019

Full-timeDeep Learning Engineer

Luminovo – Posted by Luminovo München, Oberbayern, Bayern, Germany

Job Description

About us:
At Luminovo, our mission is to make AI easily usable and widely used. We currently focus on B2B deep learning projects and building tooling to automate common deep learning workflows.

Our team is diverse, international and fun and is made up of graduates from Stanford University, ETH Zurich, TUM and CDTM. After stints at Google, Intel and McKinsey, our two founders met at Stanford University and decided to relocate to Munich in 2017 to help European businesses accelerate the adoption of deep learning.

We love to work with exceptional people on interesting problems. So far, our clients include startups from Silicon Valley, mid-sized German companies, as well as established DAX corporations.

Your role

  • We are a young start-up so the challenges our engineering team faces are quite diverse. Here are some examples of how we work:
  • Take ownership of deep learning projects from beginning (deciding on our approach, and getting or ingesting the data) to end (evaluating trained models and helping with deployment)
  • Collaborate constructively with our teammates at Luminovo throughout each project: we need creativity (to come up with ideas when things don’t work), a structured approach (to not get lost between too many ideas) and some street smarts (to make sure what we are doing is actually relevant to the business problem we are trying to solve) to turn our projects into success stories and we help each other out when one of us gets stuck
  • Stay up-to-date with the newest developments in the deep learning community and identify the right state-of-the-art approach for our next project
  • Work constructively with our clients’ stakeholders and help with effectively communicating our approach and the results of our deep learning projects
  • Take responsibility for a clean codebase and help us pioneer what software engineering best practices look like for deep learning engineers - we already use standard tools like flake8, black, pytest/tox and CircleCI, but many requirements for deep learning projects are quite different from those of a standard codebase
  • Building real-world deep learning applications that our clients can deploy immediately is just half of what we do - the other half of our time we spend thinking about how to automate the most common deep learning workflows and what tooling we can build to make our own lives easier and make sure we don’t repeat ourselves when working on the next project
  • Participate in our biweekly insight hour (basically a paper reading group, with the occasional tips and tricks session for tools like PyCharm, your terminal setup or the newest deep learning library mixed in)
  • Some of our engineers also help during the sales process when we have to conceptualize new projects and estimate the scope and feasibility of different approaches

What we value
Many of our applicants have MSc or PhDs in math, physics, EE or computer science and many of our existing teammates graduated from the best universities worldwide. Some of us are great software engineers and others eat NIPS papers for breakfast.

But we purposefully did not create one of those standard lists of minimum or preferred qualifications, because we care much more about your motivation and ability to help us accelerate the adoption of deep learning in Europe than we care just about your CV. If any of the above challenges get your juices flowing, just like they do for us, please apply!

How to Apply

If you are just as excited as we are about making AI easily usable and widely used and want to work with some of the best AI engineers in Germany, please apply at the follwing link:

Job Categories: Engineering. Job Types: Full-time.

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