Model code and data form the foundation of an AI system. Scale’s leading end-
to-end solutions for the ML lifecycle based on real-world data will continue
to set the bar for the data-centric AI movement.
We are looking for entrepreneurial Machine Learning Engineers to seed and grow
our team. Your core focus will be on Content Understanding use cases -
recommendations, discovery, marketplace trust & safety, etc. If you are
excited about shaping the future of the data-centric AI movement, we would
love to hear from you!
- Apply state of the art models developed internally and from the community, use them in production to solve problems for our customers and data labelers.
- Work with product and research teams to identify opportunities for improvement in our current product line and for enabling upcoming product lines.
- Work closely with customers - some of the most sophisticated ML organizations in the world - to quickly prototype and build new deep learning models targeted at multi-modal content understanding problems.
Ideally you’d have:
- 3+ years of model training, deployment and maintenance in a production environment.
- Strong skills in computer vision, NLP, or deep learning.
- Solid background in algorithms, data structures, and object-oriented programming.
- Strong programing skills in Python, experience in Tensorflow or PyTorch.
- Strong written and verbal communication skills.
Nice to haves:
- Experience with deep learning with large scale video processing.
- Published research in areas of machine learning at major conferences and/or journals.
- Experience working with cloud technology stack (eg. AWS or GCP) and developing machine learning models in a cloud environment
- Experience working on recommendation engines
The salary range for our Tier 1 locations of San Francisco, Seattle, & New
York is $200,800.00 - $251,000.00