Job Description

General information

Legal company

Framatome is an international leader in nuclear energy recognized for its innovative, digital and value added solutions for the global nuclear fleet. With worldwide expertise and a proven track record for reliability and performance, the company designs, services and installs components, fuel, and instrumentation and control systems for nuclear power plants. Its more than 20 000 employees work every day to help Framatome's customers supply ever cleaner, safer and more economical low-carbon energy. Visit us at www.framatome.com, and follow us on Twitter: @Framatome_ and LinkedIn: Framatome.
Framatome is owned by the EDF Group (80.5%) and Mitsubishi Heavy Industries (MHI – 19.5%).

Reference number

2026-25329

Publication date

3/4/2026

Category

TA - DESIGN & ENGINEERING - TAH - Safety, process and systems design - Reactor operation & functional design

Job Opening Title

VIE - Digital Engineer F/H

Job type

[France] VIE

Salary range

Barème Alternance, Stage et VIE

BU description

S'appuyant sur plus de 40 années de savoir-faire, et les compétences de 5 000 collaborateurs à travers le monde, la Business Unit (BU) Fuel développe, conçoit, fabrique et commercialise des assemblages de combustible ainsi que des services associés au combustible, pour les centrales de production d'électricité de type réacteur à eau légère (REP pour les réacteurs à eau sous pression et REB pour les réacteurs à eau bouillante) et les réacteurs de recherche.
La BU Fuel est également en charge de l'élaboration du zirconium et de ses alliages et commercialise aussi des services d'ingénierie et des services sur site associés au combustible.

Job description

Location: [Lynchburg, VA, USA]
Department: Fuel Design
Job Type: VIE - Full-time

About the Role:

We are seeking a highly motivated AI/Digital Engineer to join our Fuel Design team in transforming how data and machine learning are applied within the nuclear fuel cycle This role focuses on applying advanced machine learning (ML) and AI techniques to support and enhance decision-making in areas such as fuel cycle optimization, core design, inventory management, and operational forecasting

You’ll work closely with nuclear engineers, data scientists, and software developers to build, deploy, and maintain AI-powered tools and models that solve complex business and engineering challenges.

Key Responsibilities:

• Propose, develop, and implement AI/ML models to solve real-world problems in nuclear fuel management, including:
  • Fuel loading pattern optimization
  • Burnup and depletion prediction
  • Fuel inventory planning
  • Anomaly detection in reactor operations
• Collaborate with subject matter experts to translate nuclear domain knowledge into model features and constraints.
• Design experiments and simulations using physics-informed machine learning or integrate ML with reactor simulation tools.
• Clean, preprocess, and analyze large datasets (e.g., simulation outputs, operational data).
• Build and maintain custom Gym environments or RL frameworks for nuclear fuel design and optimization.
• Communicate findings through visualizations, dashboards, and technical reports for both technical and non-technical stakeholders.
• Work cross-functionally with engineering, operations, and business units to integrate ML tools into workflows and decision systems.
• Stay current with advancements in AI/ML and evaluate their applicability in the nuclear sector.

Profile

Qualifications:

Required:

• B.S. or M.S. in Computer Science, Data Science, Nuclear Engineering, Applied Mathematics, or a related field.
• Demonstrated experience applying automation (using e.g., Python or Bash) on Linux systems to accelerate workflow and enhance data analysis.
• Strong understanding of runtime optimization and parallel computing in a HPC environment.
• Proficiency in Python and ML libraries such as scikit-learn, TensorFlow, PyTorch, or Stable-Baselines3
• Experience with data handling tools (e.g., NumPy, Pandas, SQL).
  Strong understanding of supervised, unsupervised, and r einforcement learning methods.
• Familiarity with optimization algorithms, constraint handling, and evolutionary computation.
• Ability to explain technical details clearly to non-experts and collaborate across disciplines.

Preferred:

• PhD in Computer Science, Data Science, Nuclear Engineering, Applied Mathematics, or a related field.
• Knowledge of regulatory or economic constraints in nuclear fuel supply chains.

Job location

Job location

USA, Virginia, Lynchburg

Job location (site)

Lynchburg

BU (Organization)

FL - FD

Applicant criteria

Minimum level of education required

Master

Minimum level of experience required

Student

Employment level

Cadre

Languages

• French (Good knowledge)
• English (Good knowledge)

Extra informations

Background checking required ?

Yes

Poste soumis à autorisation au titre du contrôle des exportations

Yes