AI Production Engineer - Term

The Advanced Photon Source (APS) (https://www.aps.anl.gov/) at Argonne National Laboratory invites applicants for a one-year term AI Production Engineer position. This entry-level role will help move artificial intelligence (AI) and machine learning (ML) models developed by APS teams into reliable production use across the facility.

• The successful candidate will work with scientists and AI developers to deploy and operate AI capabilities across the APS, spanning real-time analysis of high-rate x-ray data, AI-guided experiment steering, and extraction of scientific knowledge from measurements.

• The role will support physics-aware and foundation models for imaging, diffraction, and spectroscopy; large-scale and streaming inference from HPC training environments to GPUs at instruments; and local LLM/VLM inference and agentic workflows.

• Responsibilities include optimizing inference performance, validating accuracy and generalization, integrating models into experimental workflows, monitoring model quality and data drift, maintaining model and data versions, maintaining AIOps workflows in the CAI group, and implementing AI-specific CI/CD.

• The appointee will also support closed-loop and continual-improvement workflows that use new data and human feedback to improve validated models over time.

• May be required to perform other duties as assigned.

This position is part of the Computational science and AI group (CAI) (https://cai.xray.aps.anl.gov/), a cross-disciplinary team with expertise in machine learning, large-scale AI inference, high-performance computing, and x-ray science. The appointee will collaborate across the APS, receive guidance from experienced scientists and AI developers, and contribute reliable facility-wide AI capabilities.

Candidates are encouraged to include a cover letter in addition to a CV.

• Bachelors and 0+ years’ experience, Masters and 0+ years’ experience, or equivalent

• Bachelor’s degree in Computer Science/Engineering.

• Hands-on Python experience for AI/ML through coursework, projects, internships, or employment.

• Familiarity with PyTorch and running trained neural-network models for inference.

• Understanding of ML concepts including training, validation, model evaluation, overfitting, and performance metrics.

• Ability to learn model versioning, automated validation, and AI-specific CI/CD practices.

• Ability to model Argonne’s core values of impact, safety, respect, integrity, and teamwork.

• Interpersonal skills, oral and written communication skills, and ability to interact with people at all levels both within and outside the laboratory.

Preferred:

• Experience running open-source LLMs or VLMs locally using Hugging Face Transformers, vLLM, llama.cpp, or similar frameworks.

• Experience with batched, streaming, or distributed inference and improving throughput, latency, or memory use.

• Familiarity with continual learning, active learning, automated evaluation, or feedback-driven model improvement.

• Familiarity with GPUs, Linux, containers, or high-performance computing environments for AI workloads.

• Experience with scientific data and monitoring model quality, data drift, or inference performance.

Please note that the pay range information is a general guideline only. The pay offered to a selected candidate will be determined based on factors such as, but not limited to, the scope and responsibilities of the position, the qualifications of the selected candidate, business considerations, internal equity, and external market pay for comparable jobs. Additionally, comprehensive benefits are part of the total rewards package.

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As an equal employment opportunity employer, and in accordance with our core values of impact, safety, respect, integrity and teamwork, Argonne National Laboratory is committed to a safe and welcoming workplace that fosters collaborative scientific discovery and innovation. Argonne encourages everyone to apply for employment. Argonne is committed to nondiscrimination and considers all qualified applicants for employment without regard to any characteristic protected by law.