ML Ops Engineer, Engineering Services
- Compensation
- Not disclosed
- Location
- Sunnyvale, California, United States
- Work setup
- Onsite
- Seniority
- Not specified
- Employment
- Full time
- Experience
- 7+ years
- Category
- Devops
- Posted
Skills
Must have
- 7+ years in ML infrastructure or MLOps engineering.
Nice to have
- Robotics or autonomy model deployment.
Full description
About Knightscope
Knightscope (NASDAQ: KSCP) is a security technology company building the nation's first Autonomous Security Force: autonomous machines, AI-driven software, and elite security professionals operating as one integrated managed service. The Company is on a mission to make the United States of America the safest country in the world. One Team. One Force.
Job Summary
You will build the MLOps function that Knightscope needs but does not yet have. K7 autonomy, Signals ICM 2.0 detection, Digital Twin, and OpenExO all depend on production ML, and today each improvises alone. You will own the shared infrastructure that lets all of them ship, monitor, and improve models reliably.
Location: ONSITE - Sunnyvale, CA
About the Role
You will build the MLOps function that Knightscope needs but does not yet have. K7 autonomy, Signals ICM 2.0 detection, Digital Twin, and OpenExO all depend on production ML, and today each improvises alone. You will own the shared infrastructure that lets all of them ship, monitor, and improve models reliably.
Key Responsibilities
- Build the production ML deployment, monitoring, and observability pipeline across programs.
- Absorb the data pipeline scope originally scoped as a separate hire.
- Partner with the Signals ML/CV Engineer on ICM 2.0 production infrastructure.
- Partner with K7 ML engineers on autonomy model deployment.
- Establish MLOps standards and SDLC through the Center of Engineering Excellence.
Required Qualifications
- 7+ years in ML infrastructure or MLOps engineering.
- Strong experience productionizing models at scale.
- Model monitoring, drift detection, and observability.
- Data pipeline engineering experience.
- Comfort supporting multiple product teams from shared infrastructure.
Nice to Have
- Robotics or autonomy model deployment.
- Computer vision model production experience.
- Prior work standing up an MLOps function from scratch.
Compensation and Benefits
Base Salary: $180,000 to $210,000 (DOE)
Equity: Stock options
Benefits: Medical, dental, vision, 401(k), paid time off
Location Requirement: Full-time, on-site at Sunnyvale HQ