hum-ai - Senior Machine Learning Engineer
Requirements
• Bachelor's degree in computer science, engineering, or a related field, or equivalent experience. • 5+ years of relevant industry experience, including hands-on machine learning engineering. • Proficiency building distributed, multi-node training pipelines in PyTorch and Lightning. • Experience with AWS or another cloud platform, particularly the tooling for training and serving medium-to-large models. • Strong software engineering fundamentals: you write production-quality Python and care about reliability, observability, and cost. • Fluent with modern agentic coding tools (e.g. Claude Code, Cursor, Codex) and current on how to use them well. • Experience training large diffusion or transformer models, ideally on video or time-series data. • Experience with multimodal or spatiotemporal data, geospatial data, or geoscience problems. • Experience serving models in production and integrating them with downstream applications or agents. • Startup experience, comfortable with a small, fast-moving team.
Responsibilities
• Own the ML platform. Build and run the systems for experiment tracking, distributed training at scale, and serving inference, and keep them fast, reliable, and reproducible. • Collaborate on the interfaces. Work with our engineers and scientists to define and maintain the boundaries between data and training, data and inference, and inference and the agent. • Enable multimodal training. Build the data and model plumbing that lets us train on many sensors, observation types, and text in one model. • Go from small to large. Help our scientists prove ideas in fast, cheap experiments, then scale the winners to petabyte-scale training runs. • Make evaluation real. Implement and improve our benchmarks and evaluation frameworks, both internal and user-facing. • Watch the meter. Measure and optimize the cost and wall-clock time of experiments, training, and inference. • Support the agent. Work with the product team on how the agent calls the model and consumes its outputs, and build the integration.
Benefits
• Work that matters for the planet. Our customers in nature conservation, carbon removal, and government use our models to protect ecosystems and respond to a changing climate. We take positive impact seriously, including safety and guardrails, and you'll help us get it right. • A team worth joining. Founded at the University of Waterloo by PhDs and engineers who've built and shipped at scale, we're small, technical, and collaborative. You'll work alongside people who care about the problem as much as you do. • Well backed. $10M+ raised from HF0, Inovia Capital, and Propeller Ventures, angels including the cofounders of Firebase and OpenTable, and partners like AWS and the United Nations. • Compensation and upside. Competitive salary, meaningful early-stage equity, health, dental and vision. As one of the first AI hires, your equity stake reflects that.
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