Staff Machine Learning Engineer

at  Labelbox

Labelbox is the leading data-centric AI platform for building intelligent applications. Teams looking to capitalize on the latest advances in generative AI and LLMs use the Labelbox platform to inject these systems with the right degree of human supervision and automation. Whether they are building AI products by using LLMs that require human fine-tuning, or applying AI to reduce the time associated with manually-intensive tasks like data labeling or finding business insights, Labelbox enables teams to do so effectively and quickly.
Current Labelbox customers are transforming industries within insurance, retail, manufacturing/robotics, healthcare, and beyond. Our platform is used by Fortune 500 enterprises including Walmart, Procter & Gamble, Genentech, and Adobe, as well as hundreds of leading AI teams. We are backed by leading investors including SoftBank, Andreessen Horowitz, B Capital, Gradient Ventures (Google’s AI-focused fund), Databricks Ventures, Snowpoint Ventures and Kleiner Perkins.

As a Staff Machine Learning Engineer at Labelbox, you will be a technical leader for the team building a scalable AI platform that uses foundation models for real-world AI applications. You will be responsible for prototyping and developing production grade tools for model fine tuning, evaluation, experimentation, metrics and quality control, and alignment with human or AI feedback. You will draw on your expertise in machine learning, natural language processing, and deep learning, and how various Foundation Models, including multi-modal models, embody these technologies, to drive the success of our AI initiatives in terms of roadmap definition, architecture decisions and execution, delivering products that meet the needs of our customers.