Principal AI Engineer, Machine Learning Operations
BlackSky · Remote, USA
About this role
**Principal AI Engineer, Machine Learning Operations (MLOps)** **About BlackSky** BlackSky is a real-time intelligence company operating the world’s most advanced space-based intelligence platform. We provide satellite imagery, automated analytics, and high-frequency monitoring of strategic locations, economic assets, and events worldwide—trusted by allied military and intelligence organizations and commercial customers. **Role Overview** BlackSky is seeking a **Principal AI Engineer (MLOps)** to pioneer the next generation of space-based intelligence and real-time geospatial analytics. Reporting to the **Director of Innovative Solutions**, you’ll be the technical authority responsible for designing, scaling, deploying, and automating state-of-the-art **computer vision (CV)** and **machine learning (ML)** architectures. You’ll bridge remote sensing research and production-ready software—extracting actionable intelligence from satellite imagery, optimizing edge/cloud compute, and delivering resilient capabilities. **Preferred locations:** Herndon, VA or Seattle, WA (strong remote candidates considered). --- **Responsibilities** - **End-to-End Model R&D:** Lead full-lifecycle model engineering—from problem formulation and dataset curation through training, validation, deployment, and error analysis. - **Model Robustness & Domain Adaptation:** Improve resilience to real-world satellite conditions (off-nadir angles, low light, seasonal variation, weather distortions, dense environments, cross-sensor shifts). - **Production Integration:** Ensure models are reliably trained, versioned, deployed, monitored, and maintained in production. - **Technical Leadership & Strategy:** Communicate progress, risks, and stack to cross-functional leadership and Product partners; contribute to proposals and white papers. - **Mentorship & Engineering Culture:** Provide technical mentorship, lead design reviews and experiment planning, and foster technical excellence. - Other job-related duties as assigned. --- **Required Qualifications** - **12+ years** hands-on software engineering experience; **4+ years** building CV/ML solutions for geospatial, remote sensing, or similarly complex imagery. - Bachelor’s degree in CS/Engineering/Math or related quantitative field (or equivalent experience). - Expert proficiency in **Python** and experience building deep learning systems using **PyTorch** (or comparable modern ML frameworks). - Proven experience designing, training, evaluating, and deploying **production-grade CV models** (e.g., object detection, segmentation, change detection, classification, time-series). - Strong experience with **remote sensing imagery** and geospatial data challenges (spatial resolution, viewing geometry, sensors, environmental conditions). - Hands-on experience building **geospatial data & CV pipelines** using tools such as **Rasterio, GDAL, GeoPandas, Shapely, xarray, Zarr**, or similar. - Demonstrated ability to take CV capabilities from experimentation to production (evaluation, deployment, performance optimization). - Experience developing/operating ML workloads in **AWS** (GPU training and inference). - Strong technical communication skills across technical and non-technical stakeholders. - Ability to provide technical leadership and mentorship across teams without direct management authority. - **US citizenship required** (role supports work requiring it). --- **Preferred Qualifications** - Master’s or Ph.D. in CS/Enginee
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