Machine Learning Engineer

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About us

Scale API (YC S16) is an API for human intelligence. Our mission is to bring human intelligence to software applications. By combining machine learning and a human workforce, we’re actively bridging the gap between what software can do and what humans can do. Our current clients include Alphabet (Google), Uber, Procter & Gamble, Houzz, Gusto, and many more.

We raised our Series A from Accel and were one of the top YC companies in our batch. We have breakout revenue and traction and have been growing rapidly. We’re still a small team, and we’re hiring to build a world-class founding team. We’re from Harvard, MIT, and CMU, and previously worked at Dropbox, Quora, Snapchat, Facebook, and Palantir.

Machine Learning Engineer

We are building one of the largest hybrid human-machine systems out there. We currently complete millions of tasks a month, and that comes with a host of interesting technical challenges. Here are just a few of the challenges we face:

  • Building robust machine learning models to automate requests and improve Scaler efficiency
  • Building models to properly estimate quality of tasks and guarantee quality on requests at scale
  • Properly routing tasks from customers to Scalers for low turnaround and high accuracy
  • Building automated candidate qualification, hiring, and firing at scale
  • Creating optimized and efficient tooling for Scalers to complete hundreds of complex tasks

You should have extensive experience in at least one of the following and familiarity with all of them:

  • Deep Learning: Experience building CNNs, LSTMs, etc. to build audio and visual models
  • Classical Machine Learning: non-deep learning methods such as random forests, collaborative filtering, HMMs, etc.
  • Applied ML Engineering: Experience building large-scale data and machine-learning pipelines

Nice to haves:

  • Experience with TensorFlow
  • Experience with Python and Redshift

Apply by sending an email to [email protected] with your resume, LinkedIn, and Github.