2 months ago
Base Salary
$149k - $238k/yr
Responsibilities
- Build and ship dashboards, metrics systems, recommendation tools, and other data products that drive decisions.
- Own production ML deployment, including reliable model serving, monitoring, versioning, and operational rigor.
- Build and maintain data pipelines from TASER device telemetry through analytics surfaces for agencies and internal stakeholders.
- Set technical direction for the team’s engineering practices and serve as its senior engineering voice.
- Work across the full stack from device-side data ingestion to user-facing analytics and move between projects.
- Use AI tools as a core part of the software development workflow.
Requirements
- Write high-quality, strongly typed, comprehensively tested production code in Python.
- Have deployed and operated machine-learning systems in production, including model serving, monitoring, and failure handling.
- Have shaped technical roadmaps, influenced peers and organizational direction, and advanced goals independently.
- Be comfortable defining evolving problems and working with messy real-world data such as device logs, behavioral data, or event streams.
- Hands-on experience with ML production tooling such as model registries, serving infrastructure, pipeline orchestration, and model monitoring is preferred.
- Experience with cloud data platforms in an ML context, including Azure ML, Databricks, or Snowflake, and with batch or streaming pipeline architecture is preferred.
- Experience with hardware-adjacent data such as device telemetry or IoT event logs is preferred.
- An advanced degree in a quantitative or analytical field is preferred, and intellectual backgrounds outside computer science are valued.
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 and paid parental leave for all.
- Medical, dental, and vision plans.
- Fitness programs and emotional and mental wellness support.
- Learning and development programs and employee resource groups.
- Office snacks.