AI/ML Engineer

Sunlight reflection may be the only available option, alongside dramatic emissions reductions, adaptation, and rapid scaling of carbon removal, to rapidly limit many climate impacts over the coming decades. But we don’t know nearly enough about it to make a scientifically-informed decision about potential deployment – and we’re not on a trajectory for rapid, legitimate decision making.

Reflective is a philanthropically-funded initiative to develop the necessary knowledge base and do the requisite technology research and development, urgently and responsibly.

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What you’ll do

As an AI/ML Engineer at Reflective, you will be the technical lead for ML architecture and MLOps for our multi-scale modeling project, turning petabytes of climate and microphysics data into robust, lightning-fast surrogate models. The purpose of this project is to prototype surrogate models, machine‑learned emulators trained on targeted high‑resolution simulations, designed to increase the accuracy and speed of modeling SAI deployment scenarios. You’ll prototype transformer, diffusion, and GNN approaches, optimize training on cloud-based GPU clusters, and integrate models into Reflective’s open-source stack.

Responsibilities

• Design, implement, and benchmark surrogate architectures for atmospheric and aerosol processes using best-in-class AI/ML methodologies.
• Build reproducible data pre-processing and training pipelines (PyTorch, JAX, Lightning, Weights & Biases).
• Design and implement state-of-the-art computer vision models, including Vision Transformers (ViTs) and generative approaches like diffusion, to extract insights and build surrogates from complex climate and microphysics datasets.
• Automate hyper-parameter sweeps and uncertainty calibration on multi-GPU clusters; monitor cost vs. accuracy trade-offs.
• Containerize and document workflows so scientists can retrain or fine-tune models with minimal friction.
• Collaborate on releases, tutorials, and user-support channels; respond rapidly to bug reports

Who you are

Minimum qualifications

• You have 3+ years in applied ML engineering
• You have developed or contributed to at least one end-to-end deep-learning system that is in production or used for research purposes.
• Strong software-engineering skills (Python, Linux, GitHub Actions, Docker) and comfort with distributed training on GPUs.
• Familiarity with scientific data formats (NetCDF, Zarr) and geospatial arrays.
• Ability to explain complex ML choices to domain scientists and incorporate their feedback.
• You’re creative and attached to outcomes, not process – you’re constantly looking for new paths to the destination and excited to switch gears if there’s a faster, better way to get something done.
• You are passionate about Reflective’s mission.

Preferred qualifications

• Experience with physics-informed ML, operator learning, or uncertainty-aware surrogate modeling.
• Prior work in climate, weather, or remote-sensing ML.
• Exposure to Fortran or C++ code-bases used in Earth-system modeling
• You are able to communicate with impact and confidence, both orally and in writing.
• Ability to work in person in the SF Bay Area 2-3 days per week.

Not needed

• A nonprofit background. Reflective is technically a nonprofit, but it doesn't feel like one.

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We encourage anyone who is interested in this role to apply, regardless of whether you feel you meet 100% of the qualifications. The top candidates will bring their own unique perspectives, experiences, and backgrounds from a variety of industries along with many but not necessarily all the skills listed above. We offer professional learning and training opportunities to help you develop skills you may not have had the opportunity to cultivate yet.

Location

Our goal is to hire the right person for the role regardless of location, but we have a slight preference for candidates who can work from our Bay Area office 2-3 days/week. However, the role can be fully remote and we are open to candidates based anywhere in the world who can overlap with our core working hours. We may be able to sponsor visas for US-based foreign nationals and have a moving stipend to support candidates who would like to relocate to the Bay Area.

But regardless of location, we love seeing each other in person and believe regular co-location helps improve collaboration and team culture. As such, we plan regular team co-working weeks, typically in the Bay Area. This role may entail additional travel (up to 1x per month) for conferences, external meetings, and team gatherings. Of course, we cover those travel costs.

Compensation and Benefits

We are committed to providing competitive compensation and comprehensive benefits to our employees. We offer fixed salary levels based on experience and role to minimize biases in compensation and to ensure team members are paid the same for doing the same work.

We expect this position to be a regular, full-time position, with an annual salary between $145,000 and $210,000 USD, depending on level of experience. In addition to salary, we offer a comprehensive set of benefits to all full-time employees:

• Medical, dental, vision insurance
• 401(k)
• Professional and personal development
• Generous paid time off and sick leave, including 12 weeks paid parental leave
• Flexible working hours

Diversity

At Reflective, recruiting, hiring, mentoring, and retaining a diverse workforce is critical to our success. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran. 

Reflective is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.