Sr. ML Engineer- Demographics & Socioeconomic Modeling

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Design, develop, and iterate on geospatial AI/ML models for demographic estimation, socioeconomic measurement, and related domains—grounded in peer-reviewed methodology and validated against real-world ground truth.
Experiment across model architectures, feature sets, and data sources (satellite imagery, geospatial signals, survey data) to push the frontier of what’s possible in data-scarce environments.
Document your methods and results clearly so that partners, collaborators, and teammates can understand, trust, and build on your work.

Write clean, well-tested, maintainable code using professional engineering practices—not just notebooks and prototypes.
Work within Atlas AI’s engineering stack (GCP cloud infrastructure, CI/CD, workflow orchestration) to deliver robust, scalable model outputs that power the Aperture® Platform.
Own your workstream end-to-end: break complex projects into components, set milestones, hit deadlines, and coordinate cross-functionally with engineering and product teammates.

Work directly with Atlas AI’s partners across academia, commercial customers, governments, and international development organizations.
Bring a customer-first mindset: understand partner needs deeply, communicate progress transparently, and deliver results that earn trust.
Represent Atlas AI’s technical capabilities in partner meetings, technical reviews, and collaborative research.

Manage projects and workstreams with accountability for timelines and outcomes.
Mentor teammates and contribute to a culture of technical excellence and continuous learning.

5+ years of professional experience in ML/AI, with a meaningful portion focused on geospatial methods (remote sensing, spatial statistics, earth observation, or related fields).
Academic background (Master’s or PhD preferred) or equivalent deep expertise in demographics, socioeconomic modeling, population estimation, poverty measurement, or a closely related quantitative social science.
Demonstrated ability to develop ML models from the research literature through experimentation to production deployment—not just one or the other.
Strong Python engineering skills and comfort with professional development practices (version control, testing, code review, CI/CD, containerization).
Experience working with cloud infrastructure (Google Cloud) and large-scale geospatial data processing.
Track record of managing complex, multi-component technical projects with clear ownership of deliverables and deadlines.
Excellent communication skills: you can explain your methodology to a PhD collaborator, present findings to a government partner, and write documentation that an engineer can implement from.

Published research in geospatial AI, demographic modeling, or related fields.
Experience building data products or platforms for users in low- and middle-income countries (LMICs).
Familiarity with global survey datasets (DHS, LSMS, census microdata) and their strengths and limitations.
Prior experience in a startup or other entrepreneurial environment.

Reports to: Chief Product Officer
Location: Remote (US or EU)
Compensation: $140,000–$175,000 base salary (benchmarked to SF/NY metro markets; adjusted by location based on cost of living and local market data) + meaningful equity in an early-stage company at an inflection point.
Benefits: We offer a flexible, distributed working environment with competitive benefits

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