Full Stack Materials Database Programmer for ML/AI Integration

Q-NEXT and the Argonne Quantum Foundry invites applications for a Full-Stack Database Programmer / Technical Developer to support the development, implementation, and maintenance of data infrastructure used in materials synthesis, model and experiment interoperability, autonomous discovery and closed-loop AI/ML frameworks. The successful candidate will contribute to improving the laboratory's quantum materials data pipeline by helping consolidate legacy, fragmented systems into a unified, high-performance, and scalable database architecture based on the LiST codebase model. Joining a dynamic, collaborative team working across Q-NEXT, Penn. State, the Argonne community, and partners at the University of Chicago, the candidate will support the acceleration of Q-NEXT's materials development thrusts and future AI/ML/modeling-forward efforts.

The primary focus of this position is to support the design and implementation of robust relational and non-relational database schemas capable of handling heterogeneous datasets, i.e. a backend robust sample lifetime tracking database. The database infrastructure will interface directly with synthesis and characterization tools, automated cluster tool platforms and automated synthesis hardware, enabling real-time data ingestion, structural logging, and API-driven access for physics-bound AI models and broader efforts focusing on leveraging both predictive, experimental, and simulated datasets.

The programmer will collaborate with post-doctoral researchers, staff scientists, and external partners such as LiST within Q-NEXT to gather data and workflow requirements, develop and test code, document database structures and software components, and assist in improving data access and query performance for project needs. Responsibilities may also include supporting application components, APIs, dashboards, and data processing workflows using established software development practices.

• Database Architecture: Experience working on scientifically focused materials databases (e.g. LiST) strongly valued. Experience in developing, normalizing, and maintaining production-grade relational (e.g., PostgreSQL, MySQL) and non-relational (e.g., MongoDB, NoSQL structures) databases.
• Full-Stack Development: Experience with backend development in C#, .NET, or Python (FastAPI, Flask, or Django), and familiarity with frontend technologies such as React or Next.js to support internal data dashboards and visualization tools.
• Data Integration: Experience supporting automated data pipelines, streaming data ingestion and interfacing code with experimental hardware or instrumentation control systems.
• Communication & Collaboration: Excellent written and oral communication skills; ability to work effectively within an interdisciplinary team of physicists, materials scientists, and automation engineers.
• Data Science & Analytics: Experience with data curation and version control via Git.
• Infrastructure & DevOps: Experience with containerization (Docker, Kubernetes) and deploying applications within enterprise or cloud-based scientific computing environments.
• Domain Awareness: Experience working with heterogeneous scientific data and metadata formats (e.g., HDF5, JSON, raw instrument logs) or working within a research/laboratory environment.
• Normal daytime work hours at the Argonne site; occasional travel and some overtime may be required. Remote work is optional.
• Ability to work independently on assigned tasks under general supervision.
• High adherence to evidence-based software architecture and clean code practices.
• Ability to model Argonne's core values of impact, safety, respect, integrity and teamwork.
• PT2: Bachelor's degree with 2+ years of experience, or equivalent.

Desired knowledge, skills and experience:

• Familiarity with machine learning loops or active learning frameworks.
• Familiarity with orchestration tools (e.g., Airflow, Prefect) for managing scientific data workflows.
• Knowledge of web security protocols, user authentication (OAuth2, JWT), and role-based access control.

Argonne employees, and certain guest researchers and contractors, are subject to particular restrictions related to participation in Foreign Government Sponsored or Affiliated Activities, as defined and detailed in United States Department of Energy Order 486.1A. You will be asked to disclose any such participation in the application phase for review by Argonne's Legal Department. All Argonne offers of employment are contingent upon a background check that includes an assessment of criminal conviction history conducted on an individualized and case-by-case basis. Please be advised that Argonne positions require upon hire (or may require in the future) for the individual be to obtain a government access authorization that involves additional background check requirements. Failure to obtain or maintain such government access authorization could result in the withdrawal of a job offer or future termination of employment.