Machine Learning Engineer

Machine Learning Engineer

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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 that operators and engineers rely on every day. We’re growing quickly, expanding our team and 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.

• Collaborate closely with customers to understand their unique needs and tailor AI solutions to meet specific industry challenges, particularly in the nuclear and utility sectors.
• Fine‑tune pre‑trained language models for customer‑specific classification, extraction, and prediction tasks.
• Design, train, and validate custom ML pipelines to address domain‑specific problems, ensuring high accuracy and performance in real‑world applications.
• Implement and optimize ML models for deployment in production environments, focusing on scalability and efficiency.
• Partner with cross‑functional teams, including development teams and domain experts, to ensure solutions align with customer workflows and objectives.
• Continuously improve models by leveraging customer feedback and incorporating new data.
• Drive innovation in the use of AI and ML within the nuclear and utility industries by experimenting with cutting‑edge techniques and tools.

• 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.

• Prior experience working in a startup environment.
• Knowledge of the nuclear or utility industries.

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

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

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

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Mid‑Senior level

Full‑time

Engineering and Information Technology

Software Development