Machine Learning Engineer (TS/SCI)
$165k - $215kVantor
Job Description
Vantor is forging the new frontier of spatial intelligence, helping decision makers and operators navigate what’s happening now and shape what’s coming next. Vantor is a place for problem solvers, changemakers, and go-getters—where people are working together to help our customers see the world differently, and in doing so, be seen differently. Come be part of a mission, not just a job, where you can: Shape your own future, build the next big thing, and change the world.
\n \n To be eligible for this position, you must be a U.S. Citizen. This position requires an active U.S. Government security clearance, applicants who do not currently hold the required clearance will not be eligible for consideration. Employment for cleared roles is contingent upon verification of clearance status. \nExport Control/ITAR: Certain roles may be subject to U.S. export control laws, requiring U.S. person status as defined by 8 U.S.C. 1324b(a)(3).
\n \nPlease review the job details below.
\n \nThis position requires an active U.S. Government Security Clearance at the TS/SCI level .
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Do you have a head for numbers and enjoy being an integral part of solving mission-critical, real-world problems? Do you like working with geospatial intelligence (GEOINT) data? If so, you’ll love working with us! Our solutions require innovative approaches that integrate bespoke capabilities and tools to solve our customers most complex challenges.
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Responsibilities :
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- Design, develop, and deploy multiple CV pipeline components (e.g., image preprocessing, distributed training, inferencing engine, data store, etc.) \n
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- Implement synthetic data generation capabilities using generative AI applied to commercial and government GEOINT data \n
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- Data engineering to transform various data types to support various phases of the AI/ML workflow \n
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- Staying updated on recent CV technical advances from industry and academia and applying them to customer mission problems \n
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- Briefing internal Vantor teams on delivery progress, evaluation results and project challenges \n
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Minimum Qualifications :
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- US citizenship and a current TS/SCI clearance (with willingness to get a CI Polygraph) \n
- 5+ years of programming experience with at least one general purpose programming language (Python, Typescript, Java, C/C++) \n
- 2+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience \n
- 2+ years of relevant experience in machine learning engineering, data engineering, backend software engineering, or a closely related technical role. \n
- Hands-on experience training, fine-tuning, or adapting machine learning, AI models using a modern ML framework. \n
- Experience deploying machine learning models into production, including building batch or real-time inference pipelines and managing model versions. \n
- Hands-on experience building and operating services on a major cloud platform, including managed compute, databases, storage, and identity and access management. \n
- Experience building and operating workflow orchestration using Kubernetes for data or ML pipelines. \n
- Experience owning containers, container orchestration, CI/CD pipelines, and infrastructure-as-code. \n
- Proven ability to support production systems, including debugging, observability, secure configuration, and incident response. \n
- Bachelor's degree in Computer Science, Electrical Engineering, Computer Engineering Machine Learning, or a related discipline, or equivalent demonstrated experience. \n
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Preferred Qualifications :
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- Hands-on experience with LLMs, AI agents, or agentic workflows \n
- Experience working with satellite or aerial imagery, including raster formats such as GeoTIFF, coordinate reference systems, and tools such as GDAL, Rasterio, Shapely, Fiona, and GeoPandas. \n
- Experience developing computer vision models for tasks such as object detection, semantic or instance segmentation, or change detection, ideally applied to overhead imagery. \n
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\n \n \nPay Transparency: In support of pay transparency at Vantor, we disclose salary ranges on all U.S. job postings. The successful candidate’s starting pay will fall within the salary range provided below and is determined based on job-related factors, including, but not limited to, the experience, qualifications, knowledge, skills, geographic work location, and market conditions. Candidates with the minimum necessary experience, qualifications, knowledge, and skillsets for the position should not expect to receive the upper end of the pay range.
\n \nThe base pay for this position within California, Colorado, Hawaii, New Jersey, the Washington, DC metropolitan area, and for all other states is:
\n $165,000.00 - $215,000.00\n \nBenefits: Vantor offers a competitive total rewards package that goes beyond the standard, including a robust 401(k) with company match, mental health resources, and unique perks like student loan repayment assistance, adoption reimbursement and pet insurance to support all aspects of your life. You can find more information on our benefits at:
\n \nThe application window is three days from the date the job is posted and will remain posted until a qualified candidate has been identified for hire. If the job is reposted regardless of reason, it will remain posted three days from the date the job is reposted and will remain reposted until a qualified candidate has been identified for hire.
\n \nThe date of posting can be found on Vantor's Career page at the top of each job posting.
\n \nTo apply, submit your application via Vantor's Career page.
\n \n \nEEO Policy: Vantor is an equal opportunity employer committed to an inclusive workplace. We believe in fostering an environment where all team members feel respected, valued, and encouraged to share their ideas. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, gender identity, sexual orientation, disability, protected veteran status, age, or any other characteristic protected by law.
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