Software Engineer III
Listed on 2026-02-28
-
Software Development
Software Engineer
life insurance, parental leave, paid time off, paid holidays, sick time, tuition reimbursement, 401(k)
Feb 23, 2026
Software Engineer III
Location
US-VA-Lynchburg
Category
Design and Engineering
Position Type
Full-Time
Location Type
Onsite
Posted Salary Range
USD $85,000.00 - USD $ /Yr.
Software Engineer III Location
US-VA-Lynchburg
Category
Design and Engineering
Position Type
Full-Time
Location Type
Onsite
Posted Salary Range
USD $85,000.00 - USD $ /Yr.
Why This Role Is CriticalAs the need for nuclear energy grows, the future couldn't be brighter. Join our vital mission to create lasting solutions for our planet's greatest challenges. In this role, you are ready to shape the future of clean energy and make a long-lasting global impact. With us, anticipate engaging and challenging projects that deliver innovative solutions and value-added technologies helping power more than 38 million North American homes.
You will work as an ML Systems Engineer building software for non‑destructive testing in the nuclear industry (e.g., visual, ultrasonic, eddy current). You will design the data preprocessing steps and ML model architecture to support the core function of the software. You'll collaborate with subject‑matter experts to understand the trade‑offs and specificities of the NDE workflows, adapt the architecture to them, validate the results, and ensure reproducibility of the results.
Early projects will have well‑defined scopes focused on technical execution, with more flexibility and responsibility for shaping deployment patterns as the team grows.
- Works from detailed programming specifications, designs, modifies, develops, writes and implements software‑programming applications.
- Participates in the testing process through test review and analysis, test witnessing and certification of software.
- Supports and/or installs software applications/operating systems.
- Manages installation and configuration of more complex third‑party applications.
- Provides resolution to a fundamental problem or seizes an opportunity that improves the satisfaction of a customer, user or provider.
- Explains the financial impact of a solution or a decision to assist customers in complying with budget requirements.
- May assume ownership of a specific application. Ownership = operational leadership, strategic leadership, responsible for creating and defending software design, technical leadership within a task or project that changes the software, interface with IT, vendor/consultant/subcontractor/customer management.
- May provide guidance to less experienced Software Engineers.
- Will work as an ML systems engineer building software for non‑destructive testing in the nuclear industry (e.g., visual, ultrasonic, eddy current).
- Design the data preprocessing steps and ML model architecture to support the core function of the software.
- Collaborate with subject‑matter experts to understand the trade‑offs and specificities of the NDE workflows, adapt the architecture to them, validate the results, and ensure reproducibility of the results.
- Bachelor's Degree in Computer Science, Engineering or a related field.
- At least 5 years of related experience is required, equivalent work experience may be considered in lieu of degree.
- At least 2 years in a hands‑on role in a machine learning Engineering or Data Science context.
- Can develop high‑quality work within a predefined problem scope, with emphasis on technical implementation, experimentation, and reproducibility.
- Exercises technical judgment by articulating non‑negotiables and tradeoffs, for example, classical vs. deep learning, hardware‑driven constraints, engineered vs. learned features, competing frameworks, libraries, or architectural decisions.
- Actively seeks to understand subject matter domain constraints and asks progressively better questions without being prompted to define success metrics for pilot projects.
- Assesses dataset readiness before starting model work, designs preprocessing steps, bootstraps custom model training or transfer‑learning workflows, beyond notebooks, in modular Python code including data preprocessing (for visual‑or‑audio‑like data), experiment…
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