Machine Learning Engineer

Why Nuclearn.ai

Nuclearn.ai builds AI-powered software for the nuclear and utility industries—tools that keep critical infrastructure reliable, efficient, and safe. Our software integrates AI-driven workflow, documentation, and research automation, and is already used at 60+ nuclear reactors across North America. You'll ship production code operators and engineers rely on every day.

We're growing quickly, expanding our team and our Phoenix HQ. The work is consequential: what you build helps real plants run safer and smarter.

Eligibility: U.S. citizenship or permanent residency (green card) is required due to DOE export compliance.

What You’ll Do

• Collaborating closely with customers to understand their unique needs and tailoring AI solutions to meet specific industry challenges, particularly in the nuclear and utility sectors.
• Fine-tuning pre-trained language models for customer-specific classification, extraction, and prediction tasks.
• Designing, training, and validating custom ML pipelines to address domain-specific problems, ensuring high accuracy and performance in real-world applications.
• Implementing and optimizing ML models for deployment in production environments, with a focus on scalability and efficiency.
• Partnering with cross-functional teams, including development teams and domain experts, to ensure solutions align with customer workflows and objectives.
• Continuously improving models by leveraging customer feedback and incorporating new data.
• Driving innovation in the use of AI and ML within the nuclear and utility industries by experimenting with cutting-edge techniques and tools.

What Makes You a Great Fit

• Bachelor's or Master's degree in Computer Science, Machine Learning, or a related technical field
• 2+ years of experience implementing and deploying machine learning solutions, with at least 1 year of hands-on experience with language models
• Strong programming skills in Python and experience with PyTorch
• Demonstrated ability to translate technical capabilities into practical solutions
• Experience deploying models in production environments
  

Nice To Have (not Required)

• Experience deploying models in production environments
• Prior experience working in a startup environment
• Knowledge of the nuclear or utility industries

Compensation & Benefits

• Base salary: [$]
• Equity:[% -%]
• Bonus: [%]
• Benefits: Unlimited PTO, health/dental/vision insurance

Work Model & Schedule

• Full-time, salaried
• Mon–Fri hybrid (Wed remote); expectation is ≥80% in-office (Phoenix HQ)
  

How We Hire (fast, respectful, practical)

1. 20-min intro with the founder/hiring manager to trade context and assess mutual fit
2. Practical work sample (60–90 min; a real task in our stack)
3. Team meet + peer programming (system design + collaboration)
   We aim to move from first chat to decision quickly.