2 months ago
Responsibilities
- Build and ship dashboards, metrics systems, and recommendation tools that drive decisions.
- Own production ML deployment, including reliable model serving, monitoring, versioning, and operational practices.
- Build and maintain data pipelines from TASER device telemetry to analytics surfaces for agencies and internal stakeholders.
- Set technical direction for the team’s engineering practices and provide senior engineering guidance to data scientists.
- Work across the full stack from device-side data ingestion through user-facing analytics and move across projects to build breadth.
- Use AI tools as a core part of the development workflow.
Requirements
- Write strongly typed, comprehensively tested, maintainable production code in Python.
- Have deployed and operated machine-learning systems in production, including model serving, monitoring, failure handling, and operational rigor.
- Shape technical roadmaps, influence peers and organizational direction, and advance goals independently.
- Define evolving problems and requirements while working effectively in an exploratory environment.
- Work with messy real-world data such as device logs, behavioral data, or event streams.
- Preferred: an advanced degree in a quantitative or analytical field, with intellectual backgrounds beyond computer science valued.
- Preferred: hands-on experience with model registries, serving infrastructure, pipeline orchestration, and model monitoring.
- Preferred: experience with Azure ML, Databricks, Snowflake, batch or streaming pipeline architecture, and hardware-adjacent data such as device telemetry or IoT event logs.
Benefits
- Hybrid schedule based in Seattle or Scottsdale, with onsite work Tuesday through Friday and remote flexibility on Mondays.
- Competitive salary and 401k with employer match.
- Discretionary paid time off.
- Paid parental leave for all.
- Medical, dental, and vision plans.
- Fitness programs and emotional and mental wellness support.
- Learning and development programs, employee resource groups, and office snacks.