[Hiring] ML Engineer @Vibrant Planet

Role Description

Vibrant Planet harnesses data-driven science and cloud-based technology to help make communities and ecosystems more resilient in the face of global change. Our ML Engineering team sits at the intersection of machine learning, remote sensing, and forest ecology—building the models, pipelines, and data products that power our Land Tender decision-support platform.

We are seeking a ML Engineer to build, adapt, and operationalize foundation model-based deep learning systems that estimate forest structure metrics from remotely sensed data. In this role you will:

• Fine-tune and adapt geospatial foundation models as a backbone to custom deep neural network heads.
• Integrate trained models into Vibrant Planet’s automated production pipeline.
• Maintain the surrounding data infrastructure.
• Contribute to scientific knowledge dissemination through manuscripts.
• Serve as a key cross-team link between SciDev and Data Engineering.

Qualifications

• M.S. in Computer Science, Machine Learning, Remote Sensing, Data Science, Ecology, or a related quantitative field (or equivalent work experience).
• 3+ years of experience developing, training, and deploying deep learning models (PyTorch preferred).
• Strong Python proficiency including data science stack (NumPy, pandas, xarray, scikit-learn).
• 3+ years of experience with geospatial data processing (rasterio, GDAL, geopandas, shapely).
• Experience building and maintaining data pipelines with workflow orchestration tools (Airflow, Prefect, Dagster, or equivalent).
• Proficiency with Git, GitHub, and collaborative software development practices (code review, CI/CD).
• Experience with containerization (Docker) and familiarity with cloud platforms (AWS preferred).
• Familiarity with STAC specifications and geospatial data catalog infrastructure.
• Strong written communication skills; ability to contribute to scientific manuscripts and technical documentation.
• Basic knowledge of forest ecology, remote sensing principles, or natural resource science.

Requirements

• Adapt and fine-tune custom or publicly available geospatial foundation models.
• Prepare, curate, and manage training datasets from remote sensing sources.
• Evaluate model performance using standard remote sensing accuracy metrics.
• Contribute to experiment design, hyperparameter optimization, and ablation studies.
• Integrate trained ML models into Vibrant Planet’s automated geospatial data pipeline.
• Build and maintain STAC infrastructure for data discovery and access control.
• Design and implement larger pipelines composed of many smaller DAGs.
• Maintain and improve data ingestion, preprocessing, and quality control workflows.
• Monitor pipeline health and model drift; implement alerting and automated retraining triggers.
• Develop model cards for summarization of modeling methods and performance.
• Write and contribute to scientific manuscripts.
• Serve as a cross-team link between SciDev, Data Engineering, and Product.
• Document pipelines, model architectures, and operational procedures.
• Participate in code reviews, architectural discussions, and sprint planning.
• Demonstrated ability to work collaboratively in interdisciplinary teams.
• Strong organizational skills to ensure high-quality data and clear documentation.
• Ability to self-motivate, manage time, and work independently in a remote-first environment.
• Excellent adaptive communication skills.
• Commitment to an inclusive and equitable work environment.
• Comply with Vibrant Planet’s Information Security Policy.
• Follow secure development practices and address security vulnerabilities.

Benefits

• Salary Range: $100,000 – $200,000
• Health, dental, and vision insurance
• 401(k) plan
• Unlimited PTO policy
• Company equity
• Cell phone stipend (per pay period)
• Home office setup allowance (one-time)

Company Description

Vibrant Planet is committed to diversity. We encourage applicants from all cultures, races, colors, religions, sexes, national or regional origins, ages, disability status, sexual orientation, gender identity, military, or other status protected by law to apply.

We are most interested in finding the best candidate for the job, and that candidate may come from a less traditional background, but have capacity to grow into and thrive in the position after some mentoring.

While we welcome applicants from all backgrounds, we regret that we are unable to provide visa sponsorship (including H-1B) at this time. Candidates must already be authorized to work in the U.S. without the need for sponsorship.