Senior Research Engineer

The Allen Institute for Artificial Intelligence • Seattle, WA

3d • Onsite

About The Position

OlmoEarth is growing — more partners, more use cases, and a platform that is evolving quickly. We are looking for a Senior Research Engineer who can collaborate with our partners to tailor the OlmoEarth models to a wide range of specific applications across multiple domains. OlmoEarth is an open, end-to-end platform built around a family of foundation models for Earth observation. The platform enables users to create custom fine-tuned models to detect and classify novel geospatial features, handling the full loop: imagery acquisition, annotation, distributed model training and inference, and visualization. Our partners span some of the most respected institutions working on wildfire risk, crop mapping, mangrove conservation, and forest protection. OlmoEarth sits within the AI for the Planet group at the Allen Institute for AI, a small, mission-driven team working on conservation, food security, disaster resilience, and climate solutions.

Requirements

• 2+ years of experience deploying machine learning solutions, covering the full stack of machine learning, including understanding the business case and requirements, training models, and deploying them at scale.
• Technical experience using machine learning tools, including fluency in PyTorch, experience debugging training loops and the ability to develop and deploy task-specific heads for encoders.
• Working experience with geospatial toolsets or platforms (e.g., Google Earth Engine, QGIS, ArcGIS); familiarity with remote sensing, Earth observation, or environmental science.
• Strong written communicator across a range of formats and audiences.
• Comfort navigating technical products and concepts; curiosity and self-driven learning aptitude.
• Ability to operate independently with limited supervision.
• Demonstrates a strong ownership mindset, willing to roll up their sleeves and contribute wherever needed to help the team achieve its goals.
• Effective prioritization and organization skills; demonstrated ability to build repeatable processes and operational systems.
• Uses AI tools to move faster — and knows when to question their output.

Nice To Haves

• Experience in a mission-driven, resource-constrained environment — startup urgency combined with an understanding of how organizations like NGOs, government agencies, and research institutions operate.
• Experience with self-supervised training methods for machine learning, particularly for ViT architectures.
• Comfort scanning technical literature to inform a conversation.

Responsibilities

• Work with partners to deploy OlmoEarth for their use cases, moving fluidly across the entire OlmoEarth team, working with partners, engineers and researchers.
• Make meaningful contributions to all the components of OlmoEarth’s infrastructure (from the finetuning code to model pretraining to our rslearn backend).
• Collaborate closely with partners to deploy OlmoEarth models in challenging contexts, prioritizing contexts and partners for which we don’t have immediate solutions or there’s an opportunity to standardize a high quality approach for common use cases.
• Explore novel use cases for the OlmoEarth models (e.g. post-hoc addition of new modalities, effectively leveraging embeddings in different contexts) which can unlock new use cases and partners.
• Maintain communications with key partners to ensure their success using the OlmoEarth platform.
• Communicate internally so that partner needs are clearly understood by the OlmoEarth machine learning research, engineering and partnership teams.
• Feed lessons learned when deploying models into our infrastructure, including improvements to rslearn, OlmoEarth Studio.
• Collaborate with the research team to identify and fix issues with the OlmoEarth models preventing their deployment in specific important applications.
• Continually update our model adaptation approaches to improve model performance for all our partners, including updating fine-tuning approaches, developing recipes for new applications and improving the UI so that modelling trade-offs can be better understood by users.
• Support agent evaluations and development.

Benefits

• Medical, dental, vision, and an employee assistance program.
• Health savings account plan.
• Healthcare reimbursement arrangement plan.
• Health care and dependent care flexible spending account plans.
• Company’s 401k plan.
• $125 per month to assist with commuting or internet expenses.
• $200 per month for fitness and wellbeing expenses.
• Up to ten sick days per year.
• Up to seven personal days per year.
• Up to 20 vacation days per year.
• Twelve paid holidays throughout the calendar year.
• Annual bonuses.
• Participation in the long-term incentive plan.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed