Applied Researcher 4 (AI Foundations, LLM Core and Agentic AI)

What you'll do

• Build AI foundation models through design, training, evaluation, validation, and implementation.
• Conduct applied research and collaborate across research, engineering, product, and business teams to deliver AI-powered products.
• Prepare internal technical reports or conference submissions on novel methods and findings.

What they ask for

• Currently have, or be obtaining by the scheduled start date, a PhD in a listed field or related field; alternatively, an M.S. in a listed field or related field plus 2 years of experience in Applied Research.
• Hands-on experience developing AI foundation models and solutions using open-source tools and cloud computing platforms.
• Experience building large deep learning models and expertise in at least one of: training optimization, self-supervised learning, robustness, explainability, or RLHF.
• Track record of delivering models at scale and delivering libraries, platform-level code, or solution-level code to existing products.

Nice to have

• NLP/LLM research experience, including publications related to large language model pre-training.
• Experience training or optimizing very large models, fine-tuning and deploying LLMs, or publishing at ACL, NAACL, EMNLP, NeurIPS, ICML, or ICLR.

Pay

Cambridge, MA: $218,700 - $249,600 USD (base salary); McLean, VA: $218,700 - $249,600 USD (base salary); New York, NY: $238,600 - $272,300 USD (base salary); San Jose, CA: $238,600 - $272,300 USD (base salary)

Tools

Pytorch, AWS Ultraclusters, Huggingface, Lightning

AI focus

Applied research and development of AI foundation models, including LLM pre-training, training optimization, self-supervised learning, robustness, explainability, RLHF, and fine-tuning.