Applied Scientist

Efficient hosting of large language models and parameter-efficient adapters Architectural or parameter‑efficient adaptation techniques Inference‑time steering or controllability approaches Tooling for evaluation, debugging, or model development Implement and evaluate adaptation approaches under real‑world enterprise deployment constraints such as latency, safety, privacy, policy compliance, and compute efficiency. Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 2+ years related experience (e.g., statistics, predictive analytics, research) OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field These requirements include but are not limited to the following specialized security screenings: Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 5+ years related experience (e.g., statistics, predictive analytics, research) OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research) OR equivalent experience. 1+ year(s) experience creating publications (e.g., patents, peer-reviewed academic papers). Experience contributing to open-source systems, or production deployments involving foundation model training or adaptation. Experience in one or more of the following areas: Reinforcement learning or post-training methods Distributed or large‑scale ML training systems Evaluation or benchmarking of AI systems Tool use, planning, or agentic model behaviors Deployment of AI solutions in enterprise or customer environments 1+ years of experience building scalable ML systems or pipelines for training, adapting, or deploying AI models. 2+ years of experience with Python and machine learning frameworks (e.g., PyTorch or equivalent)