Senior/Staff Machine Learning Research Scientist Generative AI

Senior/Staff Machine Learning Research Scientist Generative AI

Scale’s Generative AI ML team conducts research on models, supervision, and algorithms that advance frontier models for Scale’s applied-ML teams and the broader AI community. You will work closely with Scale’s Generative AI product team focused on accelerating AI adoption for some of the largest companies in the world.

At Scale, our research is driven by product needs. Your focus will be on developing new foundational models, algorithms, and forms of supervision for Generative AI. You will lead writing, publishing, and adoption of your work internally with applied teams. You will be involved end-to-end from the inception and planning of new research agendas. You'll be creating high quality datasets, implementing models and associated training and evaluation stacks, producing high caliber publications in the form of peer-reviewed journal articles, blogs, white papers, and internal presentations & documentation. If you are excited about shaping the future AI via fundamental innovations, we would love to hear from you!

You will:

• Publish new methods that advance frontier models/LLMs via human in the loop
• Release papers, datasets, and open source code that improve state of the art open source models
• Evaluate, adapt, and develop new state of the art language and/or multimodal foundation models

Ideally you’d have:

• A track record of high-caliber publications in peer-reviewed machine learning venues (e.g. NeurIPS, ICLR, ICML, EMNLP, CVPR, AAAI etc.)
• Interest in capability and alignment research
• At least 3 to 5 years of model training and evaluation experience
• Strong skills in NLP, LLMs and deep learning
• Solid background in algorithms, data structures, and object-oriented programming.
• Experience working with cloud technology stack (eg. AWS or GCP) and developing machine learning models in a cloud environment.
• Strong high-level programming skills (e.g., Python), frameworks and tools such as Pytorch lightning, kuberflow, TensorFlow, transformers, etc.
• Strong written and verbal communication skills to operate in a cross functional team environment and to broadcast your work efficiently and with splash
• A PhD in AI, Machine Learning, Computer Science, or related field

Nice to haves:

• Experience in dealing with large scale AI problems, ideally in the generative-AI field.
• Demonstrated research expertise in post-training methods &/or next generation use cases for large language models including instruction tuning, RLHF, tool use, reasoning, agents, and multimodal, etc.

Compensation: Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity-based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Base Salary Range: $176,000 - $300,000 USD

About Us:

At Scale, we believe that the transition from traditional software to AI is one of the most important shifts of our time. Our mission is to make that happen faster across every industry, and our team is transforming how organizations build and deploy AI. Our products power the world's most advanced LLMs, generative models, and computer vision models. We are trusted by generative AI companies such as OpenAI, Meta, and Microsoft, government agencies like the U.S. Army and U.S. Air Force, and enterprises including GM and Accenture. We are expanding our team to accelerate the development of AI applications.

We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an affirmative action employer and inclusive and equal opportunity workplace.