Job Description

Senior Machine Learning Engineer

Location: Phoenix, AZ (Hybrid - 4 days onsite, Wednesdays WFH)

Compensation: $120K-$165K base + 10% bonus + equity (0.05-0.15%, negotiable)

Start Date: Targeting offer by end of April; ideal start mid-May

Work Authorization: U.S. Citizen or Green Card holder required

About the Company

Our client is an AI company based in Phoenix, AZ, developing advanced generative AI solutions tailored to the nuclear power industry. Their flagship platform leverages large language models (LLMs) trained on nuclear-specific datasets to automate and optimize complex engineering processes. Their technology is designed with compliance, safety, and adaptability in mind-serving both cloud and on-premise environments.

About the Role

The company is hiring two Senior Machine Learning Engineers to build a novel, research-driven forecasting engine for nuclear equipment performance. The role leans heavily into research and is ideal for candidates with academic or self-directed ML research experience. You'll work on custom neural net architectures-not just off-the-shelf models-and collaborate with a small, high-impact team.

Key Responsibilities:

• Design and develop custom neural networks and LLMs
• Build a multimodal model integrating logs, signals, and performance data
• Conduct research, literature reviews, and early-stage ML experiments
• Clean datasets and contribute to both research and early production code
• Collaborate with engineers, analysts, and domain experts

Ideal Candidate Will Have:

• 3+ years working directly with LLMs in a tech/startup environment
• 5+ years total ML experience (if shifted to LLMs more recently)
• Strong understanding of time series data, diagnostics, and forecasting
• Deep experience with PyTorch and neural architecture design
• Exposure to multimodal modeling (text, audio, images, signals, etc.)
• Strong academic or independent ML research background (papers, projects, or publications)

Tech Stack:

• Must-Have: Python, PyTorch (or TensorFlow), Cloud (AWS, Azure, or GCP)
• Nice-to-Have: Docker, Linux, DevOps exposure

Perks & Benefits:

• Blue Cross Blue Shield Healthcare
• Unlimited PTO + 11 paid holidays
• Catered lunch on Fridays
• Equity options negotiable for standout candidates

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