As a Software Engineer on Rebellion's ML/AI Data & Tools Engineering team, your job is to help set vital data free.
Working with your teammates, you will collaborate with Rebellion's defense customers and third party partners to access, curate, transform, and ultimately deliver actual and synthetic datasets needed to train computer vision, natural language, and predictive machine learning models for Rebellion's entire mission product offerings - Analyze, Secure, and Transport. You will also orchestrate a stack of internal and external tools and services that enable reliable/scalable ML model production deployment, data validation, labeling, and data quality assessment.
Rebellion ML/AI is a close-knit team of multi-disciplinary software engineers responsible for applying models that detect signal in the vast amounts of noisy data that Department of Defense activity produces. Machine learning tasks include CV entity detection, classification, anomaly identification, and NLP activities across full motion video, geospatial, cyber, and networking domains. We seek talent with a keen interest in taming sprawling datasets and unlocking their latent power to deliver better decision making, faster.
This role will be based out of the Seattle, WA office. Eligibility for security clearance preferred.
We're looking for a track record of the following:
- A bachelor's degree in a quantitative field (e.g. computer science, statistics/data science, physics, or math), or a novel early career experience equivalent
- 3+ years of professional machine learning engine
- demonstrated familiarity with backend services and/or data pipelines - with clear preference for those leverageable by ML models in a production environment
- some experience in big data handling and transfer,
- familiarity with CI/CD software and using an agile framework for software deployment,
- practiced in GoLang and/or Python,
- owning problems end-to-end, while remaining eager to pick up whatever knowledge you might be missing to get the job done
You may be a good fit if you:
- have a solid understanding of building, scaling, securing, and monitoring corporate infrastructure.
- are passionate about: (1) new developments in ML applications, (2) cutting edge hardware and software/cloud improvements for ML deployment, and (3) ways to reduce bureaucratic inefficiencies around tech and data.
- self-directed, detail-oriented, and passionate about tinkering, sandboxing, and solution generation for complicated problems with bureaucratic restrictions,
- apply excellent written and videoconference communication skills - can robustly debate, outline, explain, accommodate, and compromise in documentation and discussion while keeping Rebellion values in mind,
- are eager to please an internal customer – other Rebellion product engineering teammates – by productizing machine learning for rapid adoption into multiple domains, while simultaneously developing external customer technical relationships (since that's where the data is)
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.