Activeloop (S18)
Cloud for AI.

Machine Learning Engineer

Silicon Valley / Remote
Full-time
3+ years
About Activeloop

Activeloop, an autodata company. We connect raw data to machine learning models, seamlessly. We empower data scientists to focus on training ML models, instead of messing with the data. We enable organizations to unlock the true potential of the unstructured data, faster and cheaper.

The company is founded by PhDs from Princeton University and backed by Y Combinator and other prominent investors from Silicon Valley.

About the role

Skills: Python, Distributed Systems, Deep Learning, Data Modeling, Torch/PyTorch, ML, TensorFlow

We are looking for an experienced ML engineer equipped with sophisticated software engineering skills and a proven track record in leading open-source software.

We expect you to have:

  • 3-5 years of Machine Learning/Deep Learning/HPC/Distributed Computing experience, with a working knowledge of and a passion for NumPy, PyTorch and Tensorflow including strong programming skills in Python and C++.
  • Fluency in using Git and GitHub, and a track recording effectively contributing to open source projects.
  • The ability to pick the best tool for the job and integrate an array of technologies into a reliable High Performance Computing solution.
  • Experience with cloud services and/or running machine learning models in production including knowledge of Docker, Kubernetes, CircleCI.

We expect you to:

  • To join a highly motivated, curious, hardworking explorers in the field of AI
  • Have a builder attitude - you love building cool things that matter!
  • Proven track record of executing projects against tight deadlines.
  • Work closely with the founding team in developing hyper-scalable software for ML.
  • Proactively identify and anticipate problems and provide tangible solutions.
  • Enjoy the startup journey towards building endurable, scalable business.

About Activeloop

Today delivering valuable insights from unstructured data is difficult. It takes on average an entire month to take a model from research to production. Data scientists and engineers spend a lot of time on managing data. An overwhelming number of tools in use leads to lack of uniformity and repeatability. There is no industry standard for storing unstructured datasets. This leads to heavily manual systems that require constant data wrangling.

Activeloop, an autodata company. We connect raw data to machine learning models, seamlessly. We empower data scientists to focus on training ML models, instead of messing with the data. We enable organizations to unlock the true potential of the unstructured data, faster and cheaper.

The company is founded by PhDs from Princeton University and backed by Y Combinator and other prominent investors from Silicon Valley.

Technology

We are building Data 2.0 https://github.com/activeloopai/Hub

The landscape of computation resources across different special hardware and cloud providers is becoming increasingly fragmented.

We're building a platform that unifies and abstracts away infrastructure for easier and highly efficient machine learning and deep learning.

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