Senior Data Scientist

Boeing•Arlington, VA

6d•Hybrid

About The Position

We are looking for an experienced and technically proficient Senior Data Scientist specializing in Generative AI (GenAI) to drive the development and optimization of advanced GenAI models within BDS. This role requires a strong background in machine learning and large language models (LLMs) and offers the chance to lead projects that shape AI-driven applications. This role is in Seattle, WA or Arlington, VA. This position is Hybrid Role. The selected candidate will be required to work on-site at one of the listed location options. This position is for 1st shift. This position must meet export control compliance requirements. To meet export control compliance requirements, a “U.S. Person” as defined by 22 C.F.R. §120.15 is required. “U.S. Person” includes U.S. Citizen, lawful permanent resident, refugee, or asylee.

Requirements

Bachelor’s degree in computer science, Machine Learning, Applied Mathematics, Computer Engineering, Software Engineering, Artificial Intelligence, Physics or a closely related field.
5+ years of experience in deep learning frameworks
1+ year of experience fine-tuning open-source LLMs and integrating APIs from commercial providers.
5+ years of programming experience in Python, and experience with data engineering workflows (e.g., Spark, Airflow, SQL)

Nice To Haves

Master's or PhD in Computer Science, Machine Learning, Applied Mathematics, Computer Engineering, Software Engineering, Artificial Intelligence, Physics or a closely related field
Experience fine-tuning open-source models and integrating APIs from commercial providers.
Experience with deep learning frameworks (e.g., PyTorch, TensorFlow).
Experience in AI ethics and governance in generative models.
Experience with data engineering tools (e.g., SQL, Spark)

Responsibilities

Lead the development and deployment of advanced GenAI models, including LLMs and multi-modal systems.
Design and implement robust pipelines for model fine-tuning and evaluation.
Develop and evaluate prompt engineering strategies and embedding techniques.
Prototype and productionize GenAI applications that solve complex business problems.
Own model performance evaluation and bias/fairness assessments to ensure ethical deployment.
Collaborate with MLOps and engineering teams to scale model inference and monitor performance.
Provide insights on GenAI strategy, tools, and industry trends to the team.
Mentor junior and mid-level data scientists and contribute to team development.