Machine Learning Research Engineer

Position: Machine Learning Research Engineer

Industry: Climate Intelligence

Location: San Francisco (On-site)

Salary: $150k - $200k

We're partnering with a cutting-edge organization at the intersection of artificial intelligence and climate innovation, with a goal of creating large scale physics foundation models to predict, and shape weather conditions. As a Machine Learning Research Engineer, you'll play a critical role in building scalable systems that power breakthrough environmental predictions and modeling.

Key Responsibilities:

• Design and implement innovative machine learning models and training algorithms

• Develop large-scale data pipelines and infrastructure to handle petabyte-scale, multimodal datasets

• Run and analyze complex experiments, including ablations, to improve model performance

• Rapidly prototype and iterate on ideas in a fast-moving R&D environment

• Continuously integrate new research and approaches into production-grade systems

Required Qualifications:

• Strong understanding of core machine learning principles, with depth in areas like Computer Vision, Sensor Fusion, Language Models, or Physics-informed Neural Networks

• Hands-on experience training ML models and interpreting results through rigorous experimentation

• Expertise in building and optimizing high-volume data pipelines

Add point about background / indsutry exp

• Comfortable with distributed training frameworks and cloud-based infrastructure

• Curious, fast-learning, and driven to solve tough technical challenges

Desired Skills/Experience:

• Experience or interest in meteorology, computational fluid dynamics, or numerical simulation techniques

Think you're the right fit? Click 'Easy Apply' or contact us directly to learn more.

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