Scale Ai - San Francisco, CA
posted 3 months ago
The Machine Learning Engineer at Scale is tasked with integrating advanced techniques in computer vision, deep learning, deep reinforcement learning, and natural language processing into a production environment to enhance Scale's products and improve customer experiences. This role is pivotal in leveraging the company's unique access to vast datasets to deliver significant improvements to clients, particularly in the context of federal government customers. As part of a larger initiative, the engineer will contribute to building a hybrid human-machine system that supports machine learning pipelines, with the goal of scaling operations from millions to billions of tasks monthly. In this position, you will be responsible for taking state-of-the-art models developed both internally and from the broader community, deploying them in production to address specific challenges faced by customers and taskers. You will also analyze existing models in production, identify areas for enhancement, and implement improvements through retraining and hyperparameter optimization, ensuring that core model characteristics remain intact. Collaboration with product and research teams will be essential to pinpoint opportunities for enhancing current product lines and enabling new ones. Working with massive datasets, you will develop both generic models and fine-tune them for specific applications. A significant aspect of your role will involve building a scalable machine learning platform to automate the ML service, acting as a representative for the application of machine learning techniques across the engineering and product organization. The position requires a proactive approach to multitasking and a willingness to quickly learn new technologies, all while maintaining an active security clearance or the ability to obtain one.