Staff Engineer, AI

About Us

Black Sky is a real-time intelligence company. We own and operate the world's most advanced space-based intelligence platform and provide customers satellite imagery, automated analytics and high-frequency monitoring of strategic locations, economic assets and events from around the globe. Black Sky is trusted by the most demanding allied military and intelligence organizations and commercial companies to deliver foresight into critical matters that affect national security and the economy.

Black Sky's data enables governments and businesses to see, understand and anticipate change as it happens, giving them the ultimate strategic advantage so they can act quickly. Our global team works with cutting‑edge technology to make a difference around the world and prides itself on being people‑first, customer‑focused and fun.

Black Sky is seeking a Staff AI Engineer to lead the architecture, development, and delivery of mission‑critical AI solutions within customer environments. This is a hands‑on role and an opportunity to develop and shape an exciting new growth area. The ideal candidate for this role blends deep technical ownership (roadmap, R&D, AI/ML systems) with customer‑facing solution delivery (scoping, prototype‑to‑production, and executive communication).

This senior individual contributor role will partner with CV, MLOps, Data QA, Solutions, and BD teams to ensure Black Sky delivers reliable and actionable insights. The role will be full‑time based out of Herndon, VA working in our SCIF with occasional customer site commitments and will report to the Senior Manager of AI.

• Partner with CV and MLOps to design and extend components needed to ensure models are trained, versioned, deployed, monitored, and maintained reliably in customer environments.
• Collaborate with the Data QA team to define annotation standards, resolve taxonomy issues, and identify data‑quality improvements based on model failure modes.
• Independently prototype, evaluate, and deploy AI capabilities in a secure development environment.
• Communicate technical strategy, progress, risks, and opportunities clearly to leadership, cross‑functional partners, and other stakeholders.
• Contribute to proposals, white papers, and long‑term strategy, shaping future mission‑aligned geospatial AI investments.
• Own and architect the mission‑aligned roadmap for geospatial CV and applied AI, partnering with customers to translate mission requirements into technical designs and implementing core components.
• Other job‑related duties as assigned.

• Minimum of 10 years of hands‑on software engineering experience, including at least 4+ years developing and deploying applied AI/ML systems and pipelines.
• Bachelor’s degree in CS/EE/math/statistics or a related quantitative field.
• Strong proficiency in Python and modern ML/CV libraries such as PyTorch or Tensor Flow.
• Experience researching, building, and evaluating production‑ready CV models for detection, segmentation, change detection, or related tasks.
• Experience working with remote sensing imagery including geometry, radiometric normalization, augmentation, and sensor‑specific challenges.
• Hands‑on experience with geospatial tools such as GDAL, Rasterio, Geo Pandas, Shapely, xarray, or Zarr.
• Experience with modern ML infrastructure, including cloud services (e.g., AWS), containerization and orchestration platforms (e.g., Kubernetes), and the ability to adapt these systems to customer‑specific or offline environments such as secure enclaves, on‑prem systems, or air‑gapped deployments.
• Strong ability to communicate complex technical concepts to diverse audiences including leadership and technical teams.
• Must have an active US Top Secret clearance with an SCI.

• M.S. or Ph.D. in CS/EE/math/statistics or a related quantitative field.
• At least 2 years of experience designing, building, and operating AI/ML systems in secure, on‑prem and/or air‑gapped systems.
• Experience working in DoD, IC, or Fed/Civ environments.
• Experience designing and executing large‑scale CV experiments, including dataset construction, synthetic/augmented data…