Senior Applied Scientist

What you'll do

• Design and evaluate foundation-model adaptation methods for enterprise tasks under latency, safety, privacy, policy, and compute constraints.
• Build or contribute to post-training methods, infrastructure, and tools for steering, evaluation, debugging, and model development.
• Work with research and engineering teams to turn product and customer requirements into scalable solutions; document approaches and support team members.

What they ask for

• Bachelor's degree in a listed or related field and 4+ years of related experience, or master's degree and 3+ years, or doctorate and 1+ year, or equivalent experience.
• Ability to meet Microsoft, customer and/or government security screening requirements, including the Microsoft Cloud Background Check.

Nice to have

• Experience with foundation-model training or adaptation, including reinforcement learning, post-training, scalable ML systems, evaluation, or enterprise deployment.
• 2+ years building scalable ML systems or pipelines and 2+ years with Python and machine learning frameworks (e.g., PyTorch or equivalent).

Pay

USD $119,800 - $234,700 per year (base salary); USD $160,200 - $261,000 per year (base salary)

Tools

Python, PyTorch, RLHF, RLAIF, LoRA

AI focus

Post-training and adaptation of foundation models, including reinforcement learning, fine-tuning, architectural and parameter-efficient adaptation, inference-time steering, evaluation, and secure enterprise deployment.