Senior Machine Learning Engineer

📋 Job Overview

You'll join the small team building Bombadil and work directly on training: the data the model learns from, the architecture and training decisions that determine whether a run succeeds, and the evaluation work to measure our progress. This is a small team. You’ll drive machine learning projects from idea to production from end-to-end, rather than specializing into one piece of a much larger machine, and you’ll help build systems and practices that scale.

🏢 About The Electric Plant Co.

The Electric Plant Co. is building a new category of plant intelligence. Our Model, Bombadil, decodes those signals into real-time insights about plant health, growth, and stress. Our IoT hardware measures the hidden electrical signals in plants and trees, paired with environmental data, and our foundation model. We're a small, fast-moving company working at the intersection of biology, hardware, AI, and IoT.

🎯 The Role

You'll join the small team building Bombadil and work directly on training: the data the model learns from, the architecture and training decisions that determine whether a run succeeds, and the evaluation work to measure our progress. This is a small team. You’ll drive machine learning projects from idea to production from end-to-end, rather than specializing into one piece of a much larger machine, and you’ll help build systems and practices that scale.

✅ Key Responsibilities

• Transformer training. Model architecture, data curation, training strategies, and the full lifecycle to production.
• Evaluation of the core model. Building and refining evaluations to measure progress of new model capabilities.
• Model lifecycle practices. Develop robust, repeatable model lifecycle systems for rapid iteration.

📌 Required Qualifications

• Has built and trained transformer models from scratch, not only fine-tuned them, and can speak concretely to the data, architecture, and training-stability decisions involved.
• Roughly 3+ years of hands-on transformer-specific experience is ideal, generally within 5-10 years of overall ML/engineering experience.
• Has shipped or maintained ML systems in a practical capacity.
• Comfortable driving projects end-to-end, from data collection through evaluation, without a large specialized team around you.
• Strong software engineering fundamentals: you build and maintain real training and evaluation infrastructure, not just notebooks.
• Technical or scientific depth, not necessarily in CS or ML specifically.
• Comfortable being one of a very small number of people responsible for a company's core model.

⭐ Desirable Experience

• Experience with biological, environmental, or other scientific data.

🎁 Benefits

Salary range is $223k - $253k per year, with meaningful early-stage equity
Standard benefits
Full-time, in-person at our Presidio office in San Francisco

🛂 Visa & Eligibility

We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, or any other characteristic protected by applicable law.