Computer Vision & ML R&D Engineer – Nuclear Tech

BWXT; Lynchburg (VA); On-site; USD 60,000 - 90,000; Full time

Benefits offered by this job

Health & retirement benefits

Flexible work schedules

Professional development

Inclusive workplace

Mission-driven organization

Ongoing training

Job summary

BWXT Advanced Technologies (AT) is seeking a Computer Vision / Machine Learning R&D Engineer to apply ML to complex manufacturing processes for nuclear-related applications. The role is on-site in Lynchburg, VA, with substantial travel and a DOE/DOD clearance potential.

You will develop physics-informed ML models, work with image classifiers and detectors, and collaborate with engineering teams to deploy scalable pipelines and sensor systems.

Qualifications

• Bachelor’s degree required in EE, ME, physics, CS, data science, or related field.
• Experience with computer vision and ML; understanding of deep generative models (GANs, VAEs, diffusion).
• Knowledge of signal processing techniques.

Responsibilities

• Develop physics informed and constrained machine learning models integrated with machine vision classifiers to identify and classify manufacturing defects.
• Work on image classifiers, object detectors, video understanding models, multi-modal classifiers.
• Develop and improve sensor systems and hardware based on model performance.
• Collaborate with data analysts to understand data patterns and deploy model pipelines at scale.

Skills

Computer vision

Machine learning

Self-motivation

Team collaboration

Education

Bachelor’s degree in electrical engineering, mechanical engineering, physics, computer science, data science, or related field

Tools

GANs

VAEs

Diffusion models

Signal processing techniques

Job description

BWXT Advanced Technologies (AT) is seeking a Computer Vision / Machine Learning R&D Engineer to apply ML to complex manufacturing processes for nuclear-related applications. The role is on-site in Lynchburg, VA, with substantial travel and a DOE/DOD clearance potential.

You will develop physics-informed ML models, work with image classifiers and detectors, and collaborate with engineering teams to deploy scalable pipelines and sensor systems.