Machine Learning Engineer

Posted 7 Days Ago
Phoenix, AZ
In-Office
Junior
Artificial Intelligence • Cloud • Information Technology • Analytics • Business Intelligence • Cybersecurity • Automation
Artificial Intelligence for the Nuclear Power Industry. Augment your people. Accelerate your processes.
The Role
The Machine Learning Engineer will collaborate with customers to tailor AI solutions, design and optimize ML pipelines, and drive innovation in the nuclear and utility sectors.
Summary Generated by Built In
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.

Top Skills

Python
PyTorch
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The Company
HQ: Phoenix, Arizona
18 Employees
Year Founded: 2020

What We Do

With over 60 reactors around the world relying on our technology, Nuclearn is built on one simple idea: nuclear deserves better tools. Our team—made up of nuclear professionals and engineers—set out to modernize the industry by applying AI to some of its most critical, and often outdated, processes.

“We saw this massive gap,” said Bradley Fox, CEO and co-founder. “You’ve got the tech to split atoms, but a lot of the supporting work is still done with decades-old systems. We knew AI could help streamline that complexity—making things safer, faster, and more efficient. It’s a win for the plants, and for the future of clean energy.”

Jerrold Vincent, our CFO and co-founder, adds: “Back in 2016, we recognized the potential for AI to support nuclear—not just in cutting costs, but in preparing the next generation of workers. That’s why we started Nuclearn. We believe AI is one of the best tools we have to keep nuclear strong for the long haul.”

The software we’ve built isn’t generic. It’s nuclear-specific, pre-trained, and ready to go—designed by people who’ve lived the process and know exactly what this industry needs.

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