Company

Doublepoint creates cutting-edge interaction technology for next generation user interfaces on smartwatches, TV’s and AR. Our smartwatch algorithms detect subtle hand gestures that have not previously been possible, but to make it work flawlessly and continuously improve, we need to conduct large scale machine learning experiments flexibly and rigorously.

Role and Motivation

Doublepoint is looking for a Senior ML Ops Engineer to join our Algorithm Team. The team’s goal is to create cutting edge algorithms and develop an efficient process while doing so. They are responsible for not only the speed of iteration, but reproducibility and reporting of our model making process.

As a team member, your responsibilities will include but would not be limited to:

• Setting up and maintaining data ingestion and transformation pipelines for cleaning, organizing, serving and analyzing 100’s of GB of data.

• Tracking model development for reproducibility including versioning models, the data used to train and test them, as well as preprocessing stages.

• Devising and implementing continuous testing and deployment of new models onto multiple targets. This includes:

  • Creating meaningful performance analysis and comparison between models automatically

  • Testing models in real life with end users of our algorithm

  • Converting new models into various formats targeting android or embedded compute.

• Optimizing model training and testing times

Requirements

The candidate we are looking for must possess:

• A proven track record with at least 5 years of ML Ops experience or Dev Ops experience.

• Experience in engineering and deploying machine learning models into production.

• The ability to author or curate extremely easy to understand and usable code and tools for team members who are not necessarily trained in computer science, but mathematics and data science instead.

• Excellent in Python (PyTorch) and strong familiarity with numpy, pandas, plotting and cloud computing.

Our ideal candidate would also possess:

• A strong familiarity Tensorflow (lite, and micro)

• Understanding of backend technologies and non-ML infrastructure

• Strong familiarity with AWS

Join us in shaping the future of interaction.

Keywords

ML Ops, DevOps, Software Developer, Machine Learning, Data Science, Computer Science

Hiring process

1. Culture interview with CTO Jamin (30min)

2. Technical interview with Infra lead Yakko (1h)

3. Take-home challenge

4. Offer

5. Meet the team and get started