Data Systems AI/ML Engineer

Quick Facts

Role: Data Systems AI/ML Engineer (Earth Sciences Informatics)

Focus: AI/ML for discovery and usability of Atmospheric Radiation Measurement (ARM) Earth science data

Key work: LLM-based conversational interfaces, retrieval systems, and dataset development from ARM metadata

Collaboration: Cross-functional work with data science, database, software, and DevOps teams

Description

Develop AI-driven methods that make ARM atmospheric observations easier to find and use. Build training and evaluation datasets from ARM metadata and design LLM-powered conversational interfaces with retrieval that help researchers discover data efficiently. Work with engineers to move prototypes into production and grow into an AI/ML leadership role through technical deliverables and presentations.

Responsibilities

• Research, develop, and deploy AI/ML methods, including LLM-based conversational interfaces and retrieval systems for data discovery and usability.
• Build and maintain training and evaluation datasets derived from ARM metadata records.
• Collaborate with data scientists, database engineers, software engineers, and DevOps engineers to take systems from prototype to production.
• Support researchers and developers in creating tools for the ARM Data Center.
• Identify opportunities to expand existing AI/ML workflows and start new ones.
• Publish and present at workshops and conferences; help build collaborations across the ARM community.
• Follow and promote good practice in research integrity, AI/ML and software engineering, and safe/secure work per organizational policies.
• Grow into an AI/ML engineering leadership role through deliverables, platform development, technical presentations/demonstrations, and, when appropriate, inventions, patents, or copyrights.

Requirements

• BS with 2+ years of relevant experience, or MS with 1+ year of relevant experience, in a related field.
• 2+ years of Python programming experience for data processing, scripting, or ML workflows (academic/research/internship experience counts).
• Working knowledge of core ML concepts: supervised and unsupervised learning, embeddings, and model evaluation.
• Familiarity with structured data, metadata, or information retrieval concepts.
• Strong written and verbal communication skills; ability to work collaboratively in research-oriented environments.
• Interest in applying AI/ML to real-world scientific or environmental data problems.
• Visa sponsorship is not available.
• Ability to obtain and maintain a federal PIV card following a favorable Tier 1 federal background investigation.

Benefits

• Medical and retirement plans
• Prescription Drug Plan, Dental Plan, Vision Plan
• 401(k) Retirement Plan and Contributory Pension Plan
• Life Insurance and Disability Benefits
• Generous vacation and holidays; Parental Leave
• Legal Insurance with Identity Theft Protection; Employee Assistance Plan
• Flexible Spending Accounts and Health Savings Accounts
• Wellness Programs, Educational Assistance, Relocation Assistance, Employee Discounts
• Flexible work hours and on-site amenities (fitness, banking, cafeteria)