Senior Software Engineer II (TASER Data Science)
$148,500–$237,600 year
HybridWashington, United States
Job Summary
Build and ship production-grade data products, including dashboards, metrics systems, and recommendation tools that drive real decisions for law enforcement agencies. Own the full lifecycle of ML deployment, moving models from research to reliable production systems with rigorous monitoring, versioning, and failure handling. Construct and maintain data pipelines that ingest TASER device telemetry and deliver analytics to both internal stakeholders and external customers. Set technical direction for engineering practices, ensuring code is strongly typed, comprehensively tested, and reusable. Work across the full stack from device-side data ingestion to user-facing analytics, leveraging AI tools as a core part of your development workflow. This role sits within Axon's TASER pillar, where you contribute to a strategic pipeline aimed at reducing fatal officer-involved shootings.
Required Qualifications
- You write production code at a high standard — strongly typed, comprehensively tested, designed for the people who will maintain it after you
- You've deployed and operated ML systems in production: model serving, monitoring, failure handling, and the operational rigor that keeps them running
- You identify the most important technical work and go after it — you've shaped technical roadmaps, influenced peers and organizational direction, and moved goals forward with or without explicit direction
- You define the problem as much as you solve it — you thrive in a team where requirements evolve as you learn, and you see that as a feature, not a bug
- You've worked with real-world messy data: device logs, behavioral data, event streams, or similar
- Must be able to work onsite Tuesdays through Fridays, with the flexibility to work remotely on Mondays
- Some roles may also require legal eligibility to work in a firearms environment
Desired Qualifications
- Advanced degree in a quantitative or analytical field — PhDs are very welcome
- Intellectual background outside computer science is genuinely valued here: statistics, physics, engineering, biology, economics, linguistics, philosophy
- Hands-on experience with ML production tooling: model registry, serving infrastructure, pipeline orchestration, and model monitoring
- Experience with cloud data platforms in an ML context (Azure ML, Databricks, Snowflake) and batch or streaming pipeline architecture
- Experience with hardware-adjacent data: device telemetry, IoT event logs, or similar
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