ML Ops Engineer, Engineering Services
At a glance
Mid-level ML Platform & Ops role at knightscope. Sunnyvale · full-time · $180,000–$210,000 base.
aimlroles summary, based on the employer's posting.
What you'll do
- Build shared pipelines for deploying, monitoring and observing production models across programs
- Take on data pipeline work alongside the model infrastructure responsibilities
- Work with the Signals ML/CV Engineer to put ICM 2.0 production infrastructure in place
- Help K7 ML engineers deploy autonomy models, and set MLOps and SDLC standards through the Center of Engineering Excellence
What you bring
- At least seven years working in ML infrastructure or MLOps engineering
- Strong experience bringing models into production at scale
- Hands-on background with model monitoring, drift detection, observability and data pipeline engineering
- Comfort supporting several product teams through shared infrastructure
Who this fits
This mid-level role suits an engineer who can support multiple teams with shared ML infrastructure and establish MLOps practices. It is full-time and requires working on-site in Sunnyvale, California.
From the employer
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