Job Details

Satlantis is a leading-edge company specializing in high-performance satellite technology and data processing. We are at the forefront of innovation, developing advanced solutions for Earth observation and space exploration. Join our dynamic team in Gainesville, Florida, and contribute to groundbreaking projects that shape the future of satellite technology. For more information about the company, please visit www.satlantis.com .

Position Summary

We are seeking a highly motivated and experienced Senior Data Scientist with strong technical leadership to drive Satlantis US's applied AI and geospatial analytics initiatives. The ideal candidate combines rigorous statistical/ML expertise with pragmatic delivery: you will design, train, evaluate, and deploy models that operate on large-scale satellite imagery and spatiotemporal datasets. This is a hands-on role where you'll own modeling workstreams end-to-end-from problem formulation and dataset strategy to production evaluation, monitoring, and iteration-while setting scientific standards, mentoring teammates, and partnering closely with engineering, product, and mission teams. You will help ensure our models are accurate, robust, scalable, and operationally usable in real-world Earth-observation workflows.

What you'll do

• Own your developments. Own high-impact modeling initiatives (e.g., segmentation, detection, classification, retrieval, change detection, anomaly detection) over satellite imagery and derived geospatial products, delivering measurable improvements in quality and operational outcomes.
• Formulate problems and success metrics. Translate customer needs and research goals into well-scoped ML problems, define KPIs (precision/recall, IoU/F1, calibration, latency/throughput, cost), and establish acceptance criteria and test plans.
• Design datasets that win. Drive dataset strategy: labeling protocols, sampling and stratification, class imbalance handling, hard-negative mining, domain shift analysis, and ground-truth quality audits. Establish repeatable dataset versioning and documentation.
• Build robust training and evaluation pipelines. Implement reproducible experimentation, ablations, and benchmarking; develop evaluation harnesses (including geospatially aware metrics) and error analysis workflows that quickly identify failure modes.
• Advance model architectures. Apply modern deep learning approaches (transformers, encoder-decoder segmentation heads, self-supervised or foundation-model adaptation, distillation) and optimize for real constraints (resolution, swath, noise, atmospheric effects, time series).
• Operationalize ML responsibly. Partner with engineering to productionize models: packaging and serving, inference optimization, uncertainty estimation, drift detection, model monitoring, and lifecycle management (versioning, rollback, A/B, canary).
• Raise the scientific bar. Set standards for experimental design, reproducibility, reporting, and peer review; create clear technical narratives and decision memos that align stakeholders and accelerate execution.

Skills and experience (required)

• Bachelor's, Master's, or PhD in Data Science, Computer Science, Statistics, Applied Mathematics, Remote Sensing, or a related field.
• 3+ years of professional experience in data science / applied ML, including delivering models into production or operational workflows.
• Strong proficiency in Python for ML and data workflows; ability to write clean, maintainable, well-tested code.
• Deep knowledge of machine learning and statistics, including experimental design, bias/variance trade-offs, calibration, uncertainty, and rigorous evaluation.
• Hands-on experience with deep learning frameworks (PyTorch preferred; TensorFlow acceptable) and modern CV techniques for dense prediction tasks.
• Experience working with large-scale data: efficient data loading, feature pipelines, distributed training concepts, and performance-aware experimentation.
• Strong communication skills: ability to translate complex analyses into clear recommendations, align cross-functional stakeholders, and document work effectively.
• Demonstrated technical leadership: ownership of projects, mentoring, and cross-team influence.

Nice to have (preferred)

• Geospatial/satellite domain experience: GDAL/Rasterio, projections/CRS, tiling strategies, GeoTIFF/COG/NetCDF, STAC/PgSTAC, and geospatial quality considerations.
• Spatiotemporal modeling: time series or multitemporal imagery approaches, change detection, tracking, and event detection.
• MLOps / production ML: model serving, monitoring, drift detection, experiment tracking (e.g., W&B/MLflow/CometML), and workflow orchestration (Airflow/Argo/ZenML).
• Cloud & compute: experience training and running inference on AWS/GCP/Azure and on-prem HPC/cluster environments, including SLURM-managed GPU/CPU fleets and on-premises Kubernetes clusters; strong understanding of containers, distributed training, GPU scheduling, storage/performance constraints, and cost/performance tuning across heterogeneous infrastructure.
• Foundation models in Earth observation: adaptation/fine-tuning strategies, embedding-based retrieval, promptable/transfer learning approaches.
• Familiarity with data governance and quality frameworks (lineage, validation checks, dataset documentation).

Work Authorization

This role will not sponsor any employment visas. Candidates must have and maintain unrestricted legal authorization to work in the U.S. now and in the future, without requiring employer-sponsored visa support.

Location & Work Model:

Full-time, in-person position in Gainesville, Florida. You'll work closely with engineering and business teams on impactful, real-world satellite analytics and AI-helping deliver reliable, scalable capabilities that push forward the state-of-the-art in Earth observation.

Why Join Satlantis?

• Be part of a pioneering company at the forefront of space technology.
• Work on challenging and impactful projects that have real-world applications.
• Collaborate with a team of brilliant and passionate engineers and scientists.
• Competitive salary and benefits package.
• Opportunity for professional growth and development in a rapidly expanding industry.
• Enjoy the vibrant community and quality of life in Gainesville, Florida. Learn more at .