Staff AI/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 The AI/ML team is responsible for engineering end-to-end geospatial AI models, tackling the entire cycle from research and development to production deployment and monitoring. We straddle the line between data science and software engineering, collaborating with platform engineers to ensure our models are robust and scalable. We are a small, focused team aiming to turn complex spatial data into trusted, high-value decision-making tools for our clients. THE ROLE As a Staff AI/ML Engineer, you will focus on advancing our multimodal and satellite imagery capabilities. You will own the design and architecture of state-of-the-art models that turn geospatial data into critical enterprise insights. You will tackle the challenge of moving sophisticated research into high-performance, production-ready systems, and assist with complex agentic workflows. This role is built for a senior individual contributor who loves being "hands-on" while providing the technical mentorship that elevates the entire team’s output. This is you: a specialist in deep learning who balances a passion for scientific discovery with the pragmatic engineering mindset needed to ship reliable, scalable AI. HOW YOU'LL BE SUCCESSFUL Develop: Own the end-to-end design and deployment of advanced Deep Learning models; success is a seamless pipeline from raw data to production-ready insights that perform reliably at scale. Architect: Own the technical foundation of our ML infrastructure; success is a robust framework of registries and inference services that allow the team to iterate rapidly without breaking production systems. Mentor: Own the technical growth and code quality of your team; success is a high-performing, cohesive unit where best practices in reproducible research and model governance are the team standard. Align: Own the translation of product vision into technical roadmaps; success is a clear development priority list that proactively identifies architectural risks before they impact business timelines. Innovate: Own the evaluation of emerging technologies; success is the strategic integration of state-of-the-art research that provides Neural Earth a measurable competitive advantage. WHY WE VALUE YOU You translate high-level business goals into concrete AI/ML priorities, ensuring every technical effort drives the organization forward. You are a deep learning specialist who builds with scale in mind, moving beyond research to deploy reliable production systems. You bridge the gap between data science and engineering, designing pipelines that make complex geospatial data ingestion seamless. You serve as a technical lighthouse, guiding the team toward best practices and rigorous development standards. You are a proactive problem-solver who identifies architectural risks and performance bottlenecks before they impact delivery. You possess a dual-lens perspective, holding both the intricate technical details and the broad strategic vision simultaneously. You are a lifelong learner who monitors the pulse of ML research to keep our geospatial capabilities at the cutting edge. You communicate with clarity, turning complex model findings into compelling narratives for stakeholders and leadership. You bring a disciplined approach to the ML lifecycle, from initial feature engineering to post-deployment performance monitoring. You treat the team’s success as your own, mentoring others and fostering an environment of shared ownership and technical excellence. REQUIREMENTS Bachelor's or Master's in Computer Science, Statistics, Mathematics, Artificial Intelligence, or a related field 5-7 years in AI/ML or data science with a proven track record of production impact Experience working with geospatial data Proficiency in deep learning model frameworks like PyTorch for model development, training, and optimization. Ability to accommodate up to 15% travel COMPENSATION The salary range for this position is $165,000 to $196,000 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.