As an ML Engineer, you will wear multiple hats across our ML pipeline, including implementing and incorporating state-of-the-art research methods into the product, setting up core data processing infrastructure, and applying the product on customer datasets and models.
We are a small but dedicated team and expect everyone to be self-driven, comfortable working in our dynamic and fast-paced environment, and embrace the challenges we face.
Your mission
- Develop and train state-of-the-art deep learning and Explainable AI research methods
- Build interfaces between deep learning models and explainable AI approaches
- Reimplement existing methods and ensure they scale to real-world dataset sizes
- Deploy and stress-test our methods in customer settings
- Be on top of the latest research (ICML, ICLR, NeurIPS) constantly look for ways to use ML to serve our customers
What you need to succeed
- 2 - 3 years of professional experience turning ML research into production-grade code within Computer Vision, Explainable AI, or Active learning
- proficiency with at least 1 deep learning framework (Tensorflow, Keras, PyTorch, etc)
- Proficiency with Python and basic machine learning libraries (scikit-learn, numpy, scipy, pandas, etc)
- Familiarity with Linux and bash commands
- Ability to turn ideas into deeply reliable and well tested code that six months into the future other people will find easy to comprehend and modify.
- Passion for learning and applying new research.
- PhD or MS degree in Computer Science, Statistics, Applied Math, Electrical Engineering, Operations Research, Econometrics, or other related fields.
- Excellent communication, relationship skills, and a great teammate.
- Preferably based in UK or Europe
Hiring Process
Screen call (15 min)
Take-home challenge
Technical discussion (1.5h)
Chat with the Founders (1.5h)
Meet the team (1h)
Offer & References 🎉
Tenyks
