About The Company:
Our client is a rapidly growing post-Series B startup. Their mission is to accelerate the development of AI applications. Their first product is a suite of APIs that allow AI teams to generate high-quality ground truth data. Their customers include Alphabet (Google), Zoox, Lyft, Pinterest, Airbnb, nuTonomy, and many more, and they've become an industry standard for the self-driving car market.
They are building a large hybrid human-machine system in service of ML pipelines for dozens of industry-leading customers. They've currently completed millions of tasks a month, and will grow to complete billions of tasks monthly.
APIs include: Sensor Fusion, Semantic Segmentation, 2D Boxes/Polygons, Video, 3D Cuboids, Lines & Splines
As a machine learning engineer, you will:
- Create optimized and efficient tooling for taskers to complete complex tasks with speed and accuracy.
- Reliably evaluate data quality at scale.
- Intelligently route tasks from customers to specialized taskers for low turnaround and high accuracy.
- Automatically hire, train and onboard taskers.
This role could be a fit if you have experience in one of the following:
- Deep Learning: building CNNs.
- Classical Machine Learning: non-deep learning methods (random forests, collaborative filtering, HMMs, etc.)
- Applied ML Engineering: building large-scale data and machine-learning pipelines.
- Experience with TensorFlow and/or Pytorch.
- At least a Bachelor’s degree (or equivalent) in a relevant field.
- $130,000 - $200,000 (depending on experience)
For more information, please contact email@example.com