Scale AI is hiring a
Machine Learning Research Engineer

Summary

Join the ML team at Scale to develop machine learning solutions advancing the company mission. You'll work on a combination of deeply technical ML applications in production and cutting edge research problems, with opportunities to work with leading research teams and exposure to a wide range of problems within machine learning.

Requirements

• Graduating Fall of 2024 or Spring of 2025 from a PhD with a focus on Machine Learning, Computer Science, Deep Learning, Artificial Intelligence, Electronics Engineering
• LLM working experience
• Strong communication skills, written and verbal

Responsibilities

• Research and develop machine learning solutions to assist humans in the loop
• Develop systems that improve the creation of high quality ground truth data with speed and accuracy
• Research frontier data and post-training methods to advance state of the art LLMs for our customers
• Work with public Large Language models to benchmark and make custom versions for internal use cases
• Take state of the art models developed internally and from the community, use them in production to solve problems for our customers and taskers
• Take models currently in production, identify areas for improvement, improve them using retraining and hyperparameter searches, then deploy without regressing on core model characteristics
• Work with product and research teams to identify opportunities for improvement in our current product line and for enabling upcoming product lines
• Work with massive datasets to develop both generic models as well as fine tune models for specific products

Preferred Qualifications

• Have had a previous internship around Machine Learning, Deep Learning, or Computer Vision
• Experience as a researcher, including internships, full-time, or at a lab
• Strong high-level programming skills (e.g., Python) and familiarity with at least one deep learning framework
• Publications in top-tier journals such as NeurIPS, ICLR, CVPR, AAAI, etc. or contributions to opensource projects

Benefits

• Comprehensive health insurance
• Retirement benefits
• Learning and development stipend
• Generous PTO