Scale Ai - San Francisco, CA
posted 2 months ago
The goal of a Machine Learning Engineer at Scale is to bring techniques in the fields of computer vision, deep learning, deep reinforcement learning, or natural language processing into a production environment to improve products and customer experience. Our research engineers take advantage of our unique access to massive datasets to deliver improvements to our customers. We are building a large hybrid human-machine system in service of ML pipelines for Federal Government customers. We currently complete millions of tasks a month, and will grow to complete billions of tasks monthly. In this role, you will take state-of-the-art models developed internally and from the community, using them in production to solve problems for our customers and taskers. You will also take models currently in production, identify areas for improvement, enhance them using retraining and hyperparameter searches, and deploy them without regressing on core model characteristics. Collaboration with product and research teams will be essential to identify opportunities for improvement in our current product line and for enabling upcoming product lines. You will work with massive datasets to develop both generic models as well as fine-tune models for specific products, and build the scalable ML platform to automate our ML service. As a representative for how to apply machine learning and related techniques throughout the engineering and product organization, you should be able and willing to multi-task and learn new technologies quickly. This role will require an active security clearance or the ability to obtain a security clearance.