We’re hiring ML scientists and senior engineers in our SF offices and worldwide to work with us on some of the hardest problems around. Strong applied math or physics background preferred.
You’d be joining a team of seasoned folks working on research and implementation for products and services used at scale by the largest companies in the world.
Who are we? We've worked at companies like Apple and Cloudera, studied at institutions like Stanford and MIT, and scaled some of the largest sites in the world.
Our research often goes into production, and our production needs are extreme. Distributed systems expertise and deep familiarity with probabilistic data structures or tick data systems is ideal.
We are an employee-owned company with a strong focus on research, culture, and sustainable work-life balance.
Keywords: multi-objective optimization, active learning, unsupervised & weakly supervised learning, anomaly detection, reinforcement learning, semantic image analysis, meta-learning, efficient structure search, Python, TensorFlow, pyTorch, Keras, ONNX, OpenCL, Kubernetes.
We are now opening applications for our 2019 Engineering and ML Fellows programs. You have the option of working from our San Francisco, Berlin or Helsinki offices, or remotely.
ML Infrastructure Interns
An interest in mathematics and a background in developing code that other people use.
Things you will learn: Modern system design, distributed systems, ML engineering, active learning.
We do CI/CD. Disciplined testing is required. Few academic programs cover this in depth, but if you haven't worked in a similar environment before we'll teach you.
Desired skills: Python, *nix and security. We use Linux and Kubernetes extensively in production.
Machine Learning Research Fellows
Current PhD student or recent graduate with at least one year of industry or previous internship experience.
Current Post-Doctoral researcher looking for industry experience or collaboration on a project of interest.
Desired fields: CS, EE, Computer Vision, Pure/Applied Mathematics, Theoretical Physics, Quant Finance
Desired skills: Python, PyTorch/TF, distributed training. Previous published research articles. Probability, Stats, Optimization theory.