Senior Machine Learning Engineer

Job not on LinkedIn

🔥 13 hours ago

🏄 California – Remote

🏄 California – Remote

⏰ Full Time

🟠 Senior

🤖 Machine Learning Engineer

👻 Ghost score 18%

What it means: the chance that no one is really hiring for this job.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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hum.ai

WebsiteLinkedInAll Job Openings

2 - 10 employees

🤖 Artificial Intelligence

🚀 Aerospace

🔬 Science

💰 Accelerator/Incubator on 2024-06

Artificial Intelligence • Aerospace • Science

hum. ai is an organization focused on building general intelligence of the physical world by training AI models on large-scale satellite imagery. The company states it is training on thousands of terabytes of satellite imagery and positions itself in the earth observation / remote sensing space, with an emphasis on research and creating positive impact through analysis of Earth data. Its public materials highlight research, careers, and a mission around leveraging satellite imagery for understanding the physical world.

📋 Description

• Own the ML platform, including experiment tracking, distributed training at scale, and inference serving • Build and maintain fast, reliable, and reproducible ML systems • Define and maintain interfaces between data and training, data and inference, and inference and the agent • Build data and model plumbing for multimodal training across sensors, observation types, and text • Help research scientists validate ideas through fast, inexpensive experiments and scale successful approaches to petabyte-scale training runs • Implement and improve internal and user-facing benchmarks and evaluation frameworks • Measure and optimize experiment, training, and inference cost and wall-clock time • Collaborate with product engineers on how the agent calls models and consumes outputs • Build model-to-agent integrations • Work with engineering teams and AI research scientists to make models trainable, measurable, and servable at scale

🎯 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 tooling for training and serving medium-to-large models • Strong software engineering fundamentals and production-quality Python • Attention to reliability, observability, and cost • Fluency with modern agentic coding tools such as Claude Code, Cursor, or Codex • 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 and comfort working with a small, fast-moving team

🏖️ Benefits

• Meaningful early-stage equity • Health, dental and vision • Competitive salary • Positive-impact work supporting nature conservation, carbon removal, and government customers • Collaboration with a small, technical, and collaborative team • Backing and partnerships from investors and organizations including AWS and the United Nations

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