Job Description

Senior Machine Learning Engineer

Phoenix, Arizona

4 days in office, 1 day work from home

$125,000 - $160,000 + bonus

About the Company

This Series A startup is building cutting-edge AI solutions tailored for the energy industry. Their flagship platform is a generative AI system trained on extensive energy-specific data and engineered to automate critical processes in various facilities. Whether deployed on-premise or in the cloud, their technology enhances safety, efficiency, and compliance by integrating seamlessly into the highly regulated and data-intensive world of the energy sector operations.

The company is tight-knit, mission-driven, and moving fast to modernize one of the world’s most vital industries through deep learning and domain-specific intelligence.

About the Role

This company is hiring a Senior Machine Learning Engineer to join a small, high-impact ML team and help build a novel, research-heavy forecasting engine for equipment performance. This isn’t your typical production ML role — it’s ideal for candidates who enjoy academic-style research, building custom architectures from scratch, and solving hard problems that haven’t been solved before.

You’ll help design and build ML models that integrate logs, sensor data, and system interactions to help clients explain system behaviors in real time.

Role Responsibilities

• Design and build custom neural network architectures from scratch
• Develop a multimodal language model for forecasting equipment behavior using logs and performance signals
• Conduct in-depth literature reviews, define research strategies, and lead early-stage experiments
• Collaborate closely with software engineers, analysts, and domain experts to integrate your work into real-world tools used by clients
• Write clean, production-ready code for systems that support mission-critical infrastructure

Key Skill Requirements

• Strong research background - graduate degree (Master’s or PhD) or equivalent experience in designing ML experiments, conducting literature reviews, or publishing work
• 4+ years of Machine Learning and/or LLM experience
• Deep knowledge of LLMs and multimodal modeling, especially models that work across text, time series, or image data
• Proficiency in PyTorch (or TensorFlow), with experience in building custom neural net architectures
• Fluency in Python with strong foundations in model development, training, and validation
• Cloud experience with AWS, Azure, or GCP
• Bonus: Docker, Linux, DevOps exposure

If you are interested in this position, apply to this role and send an email to Emma Spagnola at emmaspagnola@harnham.com. Please attach a resume and a short explanation on why you are a fit for this position. Thanks!

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