Senior ML Engineer

THE COMPANY We are NEURAL EARTH . We bring clarity to physical risk, enabling leaders to engage with confidence and enact resilient, business-critical decisions. Today's environmental, economic, and infrastructure challenges are deeply interconnected, yet the data required to understand these relationships is scattered across siloed and aging systems. Neural Earth enables operational execution, delivering a single decision intelligence platform that unifies planetary, governmental, and asset-level data, always on and always learning. This is technical work that requires patience. It requires teams willing to operate at the intersection of AI research, geospatial science, distributed systems, and enterprise deployment. It is also incredibly rewarding. Join us at Neural Earth — the next frontier is here. THE TEAM Neural Earth's Engineering team powers the full stack of our decision intelligence platform for physical risk. The AI Engineering function builds the technical foundations that turn raw geospatial data into actionable intelligence, from spatiotemporal deep learning to production inference at scale. Individual contributors own their domain from architecture through deployment. Your work ships directly into Neural Earth's products and reaches customers making high-stakes decisions every day. THE ROLE Neural Earth is hiring a Senior ML Engineer to design, build, and deploy state-of-the-art AI models for satellite imagery analysis, change detection, hazard prediction, and multi-modal data fusion. You will work closely with data scientists, platform engineers, and product teams. You will define ML strategy across our geospatial product suite, mentor engineers, and establish the model governance practices that make our systems reliable and trustworthy at scale. You move fluidly between cutting-edge research and shipped product and you hold the bar high on both. This is you! HOW YOU'LL BE SUCCESSFUL Architect: Design end-to-end ML pipelines from data ingestion through training, evaluation, and scalable inference, built for reproducibility, governance, and production durability. Build: Develop and deploy spatiotemporal deep learning models for satellite and aerial imagery analysis, including segmentation, classification, object detection, change detection, and multi-modal fusion. Lead: Provide technical direction and mentorship to ML engineers and data scientists, establishing best practices for model governance, responsible AI, and reproducible experimentation across the team. Research: Evaluate and apply emerging ML architectures and geospatial foundation models (Prithvi, SatMAE, Clay) to Neural Earth use cases, translating cutting-edge ideas into shipped capabilities with real customer impact. Partner: Work with Product, Science, and Platform teams to define modeling objectives and success criteria tied to real-world outcomes, and ensure models reach customers through reliable, monitored inference services. WHY WE VALUE YOU You have 5 or more years in AI/ML engineering or research with meaningful work in geospatial, remote sensing, or spatiotemporal applications. You have deep expertise with PyTorch or TensorFlow and model architectures including transformers, vision transformers, U-Nets, and diffusion models. You are proficient in Python and geospatial libraries (GeoPandas, Rasterio, GDAL, Shapely, xarray) and have deployed ML models in production at scale. You understand geospatial data formats (GeoTIFF, COG, GeoParquet, NetCDF) and have worked with multi-modal data sources including multispectral, SAR, LiDAR, and weather datasets. You have a track record of published research, open-source contributions, or shipped products that demonstrate technical leadership, not just execution. You operate fluently between research prototyping and production engineering. You can push the frontier and ship the product. You hold the bar on model governance and responsible AI. You do not deploy systems you cannot explain or validate. You make complex ML concepts accessible to product managers, science teams, and executive stakeholders without losing what matters. You invest in the engineers around you and measure part of your success by how much the team improves. You are energized by problems where the stakes are real. A model predicting structural risk is not an academic exercise. REQUIREMENTS Master's or PhD in Computer Science, Machine Learning, Geospatial Science, Remote Sensing, or a related field 5-8 years in AI/ML engineering or research, with at least 2 years focused on geospatial or remote sensing applications Proven experience building and deploying ML models in production at scale Track record of published research, patents, or significant open-source contributions in AI/ML or geospatial domains COMPENSATION The salary range for this position is $155,000 to $193,000 annually, reflecting progression within the role based on demonstrated growth and impact. At Neural Earth, we believe in pay equity, transparency, and rewarding growth. Our compensation philosophy is built on an equitable model with offers based on role, level, and expertise. This approach ensures that all employees are paid fairly and equitably without the influence of external factors like negotiation skills or previous pay history. This structure provides clarity, consistency, and alignment between pay, performance, and career development. BENEFITS At Neural Earth, taking care of our people isn't just something we strive for, it's who we are. Our comprehensive benefits package is designed to support you at every stage, whether you're advancing your career, growing your family, or planning for the future. From day one, you'll have access to: Competitive base compensation regardless of work location Company performance-based cash bonuses Majority employer-paid health, dental, and vision insurance for you and your dependents Flexible Paid Time Off (PTO) Group Life Insurance at 2x your base salary, paid by the company FSA and HSA options to maximize your healthcare dollars We know that when people feel supported, they can focus on what matters most at Neural Earth which is doing great work, growing in their careers, and making a meaningful impact.