Machine Learning Research Scientist / Research Engineer, MLDG

Scale works with the industry’s leading foundation model labs to provide high quality data and accelerate progress in machine learning research. As a Machine Learning Research Engineer, you will design next generation data pipelines and supervision strategies in close collaboration with our customers to accelerate progress in Generative AI. The ideal candidate is highly technical and well-versed in recent research progress for LLMs, while also having great communication skills, customer obsession, and passion for evangelizing new research methods. Successful candidates will become true research partners to several top foundation model labs, contributing technically and strategically to the roadmaps for the next generation of large language models.

You will:

• Collaborate closely with researchers from the top foundation model labs to design new strategies and data pipelines involving human supervision
• Partner internally with Scale’s Data Engine team to bring your research and data pipeline ideas to life
• Shape the roadmap for how post-training data is used to supervise the next generation of large language models
• Conduct experiments for new research ideas in post-training, leveraging your unique vantage point as a technical partner to several labs
• Accelerate the meteoric growth of Scale’s Generative AI Data Engine business through deep technical partnership with our customers

Ideally you’d have:

• At least 3 to 5 years of model training and/or deployment experience in a research or production environment
• Strong skills in LLMs and deep learning
• Excellent written and verbal communication skills

Nice to haves:

• Experience in dealing with large scale AI problems, ideally in the generative-AI field
• Demonstrated expertise in large vision-language models for diverse real-world applications, e.g. detection, question-answering, captioning, etc.
• Published research in areas of machine learning at major conferences (NeurIPS, ICML, EMNLP, CVPR, ICLR, etc.) and/or journals
• Strong high-level programming skills (e.g., Python) and familiarity with at least one deep learning framework
• Previous experience in a customer facing role