Machine Learning Engineer, Remote Sensing Imagery

Company:
Location: Seattle, WA

*** Mention DataYoshi when applying ***

We are seeking a Senior Machine Learning Engineer with remote sensing experience in the Seattle, Washington Office.
At Rebellion, we use science and math to empower and support our war fighters. Our team is a close-knit team of multi-disciplinary software engineers and researchers responsible for applying models that detect signals in the vast amounts of noisy data that the Department of Defense consumes. The team works on projects with a geospatial component that involve things like CV entity detection, generative models, synthetic data, and simulation across sensor types such as SAR, EO, IR, and LIDAR across all domain operations.

In this role, you will work on a product team to use state of the art techniques and create new techniques to deliver insights across sensor types. You will also work with other ML engineers to close the gap among products by identifying opportunities for shared models or services. The goal is to provide timely intelligence during strategic Department of Defense missions and their adoption and success will ensure the safety of both civilians and service members.

Clearance eligibility: An Active TS/SCI Security clearance is required, or ability to gain clearance eligibility is required.

What you'll do:

  • Work on and with the product team to identify problem areas where AI/ML is a potential solution
  • Build or incorporate SOTA models in focus areas such as object detection, semantic segmentation, and data generation (synthetic data, generative models) across multiple domains, incorporating the geospatial component where applicable
  • Build and own the full-stack for the solution provided
  • Partner and build shared solutions with Geospatial team members and the broader AI/ML teams for cross cutting capabilities


You may be fit for this role if you:

  • Have an advanced degree in a quantitative field (e.g. computer science, statistics/data science, physics, or math),
  • 3+ years of industry experience working with frameworks such as Tensorflow, PyTorch, JAX, or Keras for tasks such as object detection, semantic segmentation, or generative modeling (GANs, Autoencoders) or using those frameworks to deploy models based on the same tasks,
  • Demonstrate strong experience in Python or GoLang,
  • Understand and enjoy working with remote sensing technologies and spatial analysis to manipulate, extract, and analyze geospatial data from satellites and aircraft,
  • Are interested in the current SOTA for generative models such as GANs and Variational Autoencoders,
  • Are self-directed, detail-oriented, and enjoy figuring out the most important problem to work on,
  • Own problems end-to-end, and are willing to pick up whatever knowledge you're missing to get the job done,
  • Prioritize getting the system working, but know when it is right to take on technical debt.

Rebellion is a well-capitalized technology start-up firm that is passionate about defining and delivering modern, life-changing software products to the US Department of Defense (DoD), the UK Ministry of Defence (MoD), and their allies. At Rebellion we believe in operating what we own, we deliver all of our products as managed services, this allows our product teams to maintain operational ownership across all deployments. Expect talented, motivated, intense, and interesting co-workers.
Compensation includes meaningful equity ownership, competitive salaries, full medical coverage, disability and life insurance, and transit reimbursement.
An Equal Opportunity Employer/Veterans/Disabled.
Rebellion Defense is an equal opportunity employer and makes employment decisions on the basis of merit and business needs. Rebellion Defense does not discriminate against applicants on the basis of race, color, religion, sex, sexual orientation, gender, gender identity, national origin, veteran status, disability, or any other protected characteristic in accordance with federal, state, and local law.

*** Mention DataYoshi when applying ***

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