Principal Machine Learning Operations Engineer
About Us:
BlackSky 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. BlackSky 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. BlackSky'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.
BlackSky is looking for a Principal AI Engineer, MLOps to pioneer the next generation of space-based intelligence and real-time geospatial analytics. Reporting directly to the Director of Innovative Solutions, you will serve as the technical authority responsible for designing, scaling, deploying, and automating state-of-the-art computer vision (CV) and machine learning (ML) architectures.
In this role, you will bridge the gap between cutting-edge remote sensing research and high-performance, production-ready software. You will lead the charge in utilizing modern AI methodologies to extract actionable intelligence from satellite imagery, optimizing edge and cloud compute environments, and delivering resilient capabilities. While we would strongly prefer candidates near either our Herndon, VA or Seattle, WA offices, we are open to strong remote candidates.
Responsibilities:
- End-to-End Model R&D: Leading full-lifecycle model engineering from initial problem formulation and dataset curation to training, validation, deployment, and error analysis.
- Model Robustness & Domain Adaptation: Driving model resilience against challenging real-world satellite conditions, including off-nadir angles, low light, seasonal variations, weather distortions, dense environments, and cross-sensor domain shifts.
- Production Integration: Ensuring models are reliably trained, versioned, deployed, monitored, and maintained in production.
- Technical Leadership & Strategy: Communicating technical progress, risks, and stack to cross-functional leadership and Product partners while contributing to proposals and white papers.
- Mentorship & Engineering Culture: Providing technical mentorship, spearheading design reviews and experiment planning, and fostering a culture of technical excellence across the engineering team.
- Other job-related duties as assigned.
Required Qualifications:
- Minimum of 12 years of hands-on software engineering experience, including at least four years developing computer vision or machine learning solutions for geospatial, remote sensing, or similarly complex imagery.
- Bachelor’s degree in computer science, engineering, mathematics, or a related quantitative field, or equivalent practical experience.
- Expert-level proficiency in Python and demonstrated experience developing deep learning systems using PyTorch or comparable modern ML frameworks.
- Proven experience designing, training, evaluating, and deploying production-grade computer vision models for tasks such as object detection, segmentation, change detection, image classification, or time-series analysis.
- Strong experience working with remote sensing imagery and the unique challenges associated with geospatial data, including varying spatial resolutions, viewing geometries, sensors, and environmental conditions.
- Hands-on experience building geospatial data and CV pipelines using tools such as Rasterio, GDAL, GeoPandas, Shapely, xarray, Zarr, or similar technologies.
- Demonstrated experience taking CV capabilities from experimentation through production, including model evaluation, deployment, and performance optimization.
- Experience developing and operating ML workloads in AWS, including GPU-based training and inference.
- Strong technical communication skills with the ability to communicate architecture decisions, experimental results, tradeoffs, risks, and recommendations to both technical and non-technical stakeholders.
- Demonstrated ability to provide technical leadership and mentorship across engineering teams without requiring direct management authority.
- The work this role supports requires holding US citizenship.
Preferred Qualifications:
- Master’s degree or Ph.D. in computer science, engineering, mathematics, machine learning, remote sensing, or a related quantitative field.
- At least 15 years of hands-on software engineering, computer vision, or machine learning experience.
- Experience working with imagery from multiple commercial and government remote sensing sources, such as BlackSky, Sentinel, Airbus, Planet, or WorldView.
- Demonstrated experience optimizing ML systems for production constraints, including inference latency, throughput, memory utilization, GPU efficiency, and cost.
- Experience rapidly developing prototypes or proof-of-concept applications and communicating results through customer demonstrations, proposals, white papers, or other technical materials.
- Strong experience with modern MLOps practices, including experiment tracking, dataset and model versioning, reproducibility, automated evaluation, and production monitoring.
- Experience applying foundation models, vision-language models (VLMs), multimodal approaches, or self-supervised learning to geospatial or remote sensing problems.
- Experience adapting models across sensors, geographic regions, resolutions, collection conditions, or other significant domain shifts.
Life at BlackSky for full-time US benefits eligible employees includes:
- Medical, dental, vision, disability, group term life and AD&D, voluntary life and AD&D insurance
- BlackSky pays 100% of employee-only premiums for medical, dental and vision and contributes $100/month for out-of-pocket expenses!
- 15 days of PTO, 11 Company holidays, four Floating Holidays (pro-rated based on hire date), one day of paid volunteerism leave per year, parental leave and more
- 401(k) pre-tax and Roth deferral options with employer match
- Flexible Spending Accounts
- Employee Stock Purchase Program
- Employee Assistance and Travel Assistance Programs
- Employer matching donations
- Professional development
- Mac or PC? Your choice!
- Awesome swag
The anticipated salary range for candidates in Seattle, WA is $185,000-$215,000 per year. The final compensation package offered to a successful candidate will be dependent on specific background and education. BlackSky is a multi-state employer and this pay scale may not reflect salary ranges in other states or locations outside of Seattle, WA.
BlackSky is committed to hiring and retaining a diverse workforce. We are proud to be an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, age, national origin, sexual orientation, gender identity, disability, protected veteran status or any other characteristic protected by law.
To conform to U.S. Government space technology export regulations, including the International Traffic in Arms Regulations (ITAR) you must be a U.S. citizen, lawful permanent resident of the U.S., protected individual as defined by 8 U.S.C. 1324b(a)(3), or eligible to obtain the required authorizations from the U.S. Department of State. #LI-Remote
EEO/ Pay Transparency Statements:
https://www.dol.gov/ofccp/regs/compliance/posters/pdf/eeopost.pdf
https://www.dol.gov/ofccp/regs/compliance/posters/pdf/OFCCP_EEO_Supplement_Final_JRF_QA_508c.pdf
Skills Required
- At least 12 years of hands-on software engineering experience, including at least four years developing computer vision or machine learning solutions for geospatial, remote sensing, or similarly complex imagery.
- Bachelor's degree in computer science, engineering, mathematics, or a related quantitative field, or equivalent practical experience.
- Expert-level proficiency in Python and experience developing deep learning systems using PyTorch or comparable modern machine learning frameworks.
- Experience designing, training, evaluating, and deploying production-grade computer vision models.
- Strong experience working with remote sensing imagery and geospatial data challenges.
- Hands-on experience building geospatial data and computer vision pipelines using Rasterio, GDAL, GeoPandas, Shapely, xarray, Zarr, or similar technologies.
- Experience taking computer vision capabilities from experimentation through production, including evaluation, deployment, and performance optimization.
- Experience developing and operating machine learning workloads in AWS, including GPU-based training and inference.
- Strong technical communication skills with technical and non-technical stakeholders.
- Ability to provide technical leadership and mentorship without direct management authority.
- U.S. citizenship is required for the supported work.
- Master's degree or Ph.D. in computer science, engineering, mathematics, machine learning, remote sensing, or a related quantitative field.
- At least 15 years of hands-on software engineering, computer vision, or machine learning experience.
- Experience with imagery from multiple commercial and government remote sensing sources.
- Experience optimizing machine learning systems for inference latency, throughput, memory utilization, GPU efficiency, and cost.
- Experience rapidly developing prototypes and communicating results through demonstrations, proposals, or white papers.
- Strong experience with modern MLOps practices, including experiment tracking, dataset and model versioning, reproducibility, automated evaluation, and production monitoring.
- Experience applying foundation models, vision-language models, multimodal approaches, or self-supervised learning to geospatial or remote sensing problems.
- Experience adapting models across sensors, geographic regions, resolutions, collection conditions, or other domain shifts.
What We Do
Speed combined with actionable insights can change everything. BlackSky’s analytics platform, Spectra AI, can give you deep awareness from our satellite constellation, comprehensive collection of sensors, signals, and other critical data feeds. If situational awareness is essential for you, BlackSky can observe and detect and then help you understand and predict change. Our customers rely on BlackSky because they need to be the first to know. BlackSky’s analytics platform, Spectra AI, combines millions of data elements daily from our earth observation constellation, partner satellites, IoT, hyper-local platforms, and third-party sources. BlackSky can deliver the advantage that others can’t. When you need to make rapid, informed strategic decisions, BlackSky can make it possible.









