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HomeCompaniesBlackSkyStaff SW Engineer, Machine Learning Operations

Staff SW Engineer, Machine Learning Operations

BlackSky · Remote, USA · Remote · Active · $150,000–$180,000 / year · Greenhouse

Job facts

FieldValue
CompanyBlackSky
TitleStaff SW Engineer, Machine Learning Operations
Normalized title-
Department / teamTechnology/Product Architecture 60-165
LocationUnited States
Work modelRemote / Remote
Employment type-
Salary$150,000–$180,000 / year
Statusactive
ATS providerGreenhouse
Posted / first seen2026-06-04 / 2026-06-06
Changed / last seen2026-06-06 / 2026-06-06

Related slices

PageWhat it containsOpen
Company jobsActive postings from BlackSky.Open
Company breakdownsRole, location, ATS, and work model facets for this company.Open
ATS provider jobsActive postings observed through Greenhouse.Open
Provider filtered searchThe same provider as a filtered job collection.Open
Department jobsActive postings in Technology/Product Architecture 60-165.Open
Work model jobsActive Remote postings.Open
Lifecycle eventsOpen, update, close, and reopen events for this posting.Open
Original postingCanonical source or apply URL captured from the ATS.Open

Linked records

CompanyBlackSky
Source314ce170-5529-4a50-a81e-7d200ff4234c
ATS providerGreenhouse

Description

Staff SW Engineer, Machine Learning Operations 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 talented and creative Staff Software Engineer to support the development, operation, and capability evolution of BlackSky’s cutting-edge AI/ML Platform. As part of the BlackSky Labs team, you are instrumental in supporting the development of novel ML applications at BlackSky. You will help ensure that we deliver consistent, reliable, and relevant ML products to BlackSky’s growing user base. Your primary responsibilities will be the integration, testing, maintenance, and deployment of ML/AI products into BlackSky environments. This position is a critical element of the BlackSky AI/ML Engineering team and is expected to work collaboratively with internal satellite development teams to ensure success. The ideal candidate has geospatial software engineering, computer vision model deployment, operations, and testing experience; familiarity with satellite imagery or similar datasets; and success working in an agile development environment. Additionally, the ideal candidate has demonstrated the ability to manage their own efforts over a broad scope of work as an independent contributor. Finally, the candidate should be an independent thinker with the demonstrated ability and willingness to lean in to learn new tools, technologies, and approaches to solve new problems. This role reports to the Manager of the BlackSky labs team and while we would prefer this position to be local to our Herndon, VA office, we are open to candidates in certain remote states. Responsibilities: Deployment and integration of computer vision solutions for next-generation satellite imagery analytics. Ensure high-quality and production-ready Python or Go code. Manage cloud infrastructure and code deployment to AWS, Kubernetes, or other environments. Take part in the entire project lifecycle from requirements development to deployment. Serve as a lead on MLOps software development projects, data ETL projects, and software feature development. Collaborate with management and technical team on technical roadmap and implementation strategy. Other job-related duties as assigned. Required Qualifications: Minimum of eight years of hands-on experience as a software engineer with at least three years focused on geospatial MLOps. Bachelor’s Degree or higher in one of the following fields: computer science, mathematics, physics, statistics, or another computational field or equivalent experience. Demonstrated experience designing and building scalable production software solutions and architectures, especially for machine learning or image processing. Strong Python3 proficiency or GO proficiency and experience writing production software for data ETL, REST APIs, micro-services, geospatial, or data analytics, and cloud deployment. Experience with databases, SQL queries, and data model design especially SQL such as PostgreSQL/PostGIS. Experience writing software to integrate with third-party APIs, performing data ETL, and managing complex data at scale in relational data stores. Strong ability to communicate concepts and software system results with customers, management, and the technical team, highlighting actionable insights. Hands on experience with cloud services such as AWS EKS, S3, EC2, Aurora / RDS, SQS, SNS, Batch, etc. You may have some exposure to machine learning. While not a requirement, it would be helpful if you have studied or have worked with machine learning, statistics, computer vision and would enjoy working with Computer Vision subject matter experts. Due to program requirements, candidates must hold US citizenship. Preferred Qualifications: Over ten years of hands-on experience as a software engineer. Advanced degree in a relevant field of study. Knowledge and experience with MLOps and DataOps as a practice. Experience with distributed compute environments such as Kubernetes and Dask. Experience with on-prem or airgapped deployments. Hands on experience working with large imagery datasets including image normalization, image augmentation, raster/vector visualization, etc. Experience managing machine learning data labels or with third party platforms such as LabelBox, SuperAnnotate, ScaleAI, etc. Experience working with geospatial and image software stacks (GDAL, Rasterio, GeoPandas, Shapely, Xarray, Zarr, etc.). Experience with remote sensing datasets and image preprocessing and manipulation methods for sensors such as Sentinel, LandSat, BlackSky, Airbus, Planet, or WorldView. Hands on experience with cloud services such as AWS EKS, S3, EC2, Aurora / RDS, SQS, SNS, Batch, etc. Experience with Infrastructure solutions including (scaling and deploying models in the cloud using AWS solutions such as Kubernetes, ClearML, Nvidia Triton, Kubeflow, Torch Serve, Argo, etc.). 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 $150,000-$180,000 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/Affirmative Action 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/AAP/ 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

Full job record

Job IDac13e6c7806d355cd6bbcea20bb378c0873bbe04
Org IDcbd4a080-0905-4f5b-ac90-86eed1e14a78
Source ID314ce170-5529-4a50-a81e-7d200ff4234c
Board ID314ce170-5529-4a50-a81e-7d200ff4234c
Providergreenhouse
Provider Job Key8573452002
TitleStaff SW Engineer, Machine Learning Operations
Normalized Title
Statusactive
Activeyes
Location TextRemote, USA
DepartmentTechnology/Product Architecture 60-165
Team
Employment Type
Workplace Typeremote
Remote Policyremote
CountryUnited States
Region
City
Salary Rawsalary range for candidates in Seattle, WA is $150,000-$180,000 per year
Salary Min150,000
Salary Max180,000
Salary CurrencyUSD
Salary Periodyear
Source URLhttps://boards.greenhouse.io/blacksky/jobs/8573452002?gh_jid=8573452002
Apply URLhttps://boards.greenhouse.io/blacksky/jobs/8573452002?gh_jid=8573452002
First Seen At2026-06-06 07:32:28Z
Last Seen At2026-06-06 19:50:23Z
Last Checked At2026-06-06 19:50:23Z
Last Changed At2026-06-06 07:32:28Z
Inactive At
Source Posted At2026-06-04 19:58:30Z
Source Updated At2026-06-04 20:03:40Z
Raw Payload Uris3://job-postings-prod-raw-590183727216/raw/provider=greenhouse/board=blacksky/date=2026-06-06/2026-06-06T19-50-23-562Z-c13db74b51f18f69dabd3d2fe5991453ade8229f8bacb24f6161bcd3be5f6063.json
Event Fields
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Parsed Structured
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Extensions
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Native Structured
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  "first_published": "2026-06-04T15:58:30-04:00",
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