As the Data Tools Engineering Manager on the ML/AI Team, you will identify and integrate infrastructure necessary for liberating strategic and tactical data critical for AI/ML applications. You will build a highly agile team to enable CI/CD deployment of both 'quick-strike' capabilities and longer term persistent services. You will own 3rd party relationships around data labelling and data handoff among end-users and data consumers. These services will be leveraged internally by the Rebellion team and externally as unique offerings.
The Rebellion Machine Learning team is a close-knit team of multi-disciplinary software engineers responsible for applying models that detect signals in the vast amounts of noisy data that the Department of Defense consumes. Machine learning tasks include CV entity detection, classification, anomaly identification, and NLP activities across full motion video, geospatial, cyber, and networking domains. We seek to add an expert to the team with significant cloud-based ML model, cloud backend, and infrastructure/architecture experience.
This position will be based out of the Seattle office. Eligibility for clearance preferred.
We're looking for a track record of the following:
- an advanced degree in a quantitative field (e.g. computer science, statistics/data science, physics, or math),
- demonstrated five or more years of industry experience developing backend services and/or data pipelines leverageable by ML models in a production environment,
- demonstrated experience of hiring and leading teams of 5 or more people
- expertise in big data data handling, archiving, persistent maintenance, data security, and data labeling
- depth of knowledge leveraging Kube Flow, Apache NiFi, Apache Airflow, AWS step functions, directed acyclic graphs (DAG), or other algorithmic pipeline orchestration architectures,
- expert on CI/CD software best practices and using an agile framework for software deployment,
- fluent in GoLang and Python,
- owning problems end-to-end, and are willing to pick up whatever knowledge you're missing to get the job done,
- getting the system working, but know when it is right to take on technical debt.
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. You could easily give a company-wide Lunch-and-Learn on some aspect of this interest.
- self-directed, detail-oriented, and passionate about tinkering, sandboxing, and solution generation for complicated problems with bureaucratic restrictions,
- apply excellent written communication skills - can robustly debate, outline, explain, accommodate, and compromise in documentation and discussion while keeping Rebellion Manifesto principles in mind.
- are eager to please an internal customer – other Rebellion product engineering teammates – by productizing machine learning for rapid adoption into multiple domains.
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.