ML Ops Engineer, Engineering Services
Sunnyvale, California, United States
- Pay
$180,000–210,000/year · BaseAnnual period assumed — pay source
Compensation and Benefits Base Salary: $180,000 to $210,000 (DOE) Equity: Stock options
Read the full posting- Work setting
- Not stated
- Employment
Full-time — employment source
Employment type in the employer’s posting: Full-Time
From the employer’s posting
What you’ll work on
Full postingYou will build the MLOps function that Knightscope needs but does not yet have.
Build production ML deployment, monitoring, and observability pipeline across programs
Own the data pipeline scope originally planned 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
Set MLOps standards and SDLC through the Center of Engineering Excellence
From the employer’s posting
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.
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.
What you’ll bring
All qualificationsCore experience
- 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
Qualification wording
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.
Benefits in the posting
Full benefits wording- Equity: Stock options
From the employer’s posting.
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.
In the employer’s words · Read in context
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Oct 7, 2026 · 22 days ago
- Recorded sightings
- 19
- Last seen by us
- Oct 30, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Your next step
- Have your resume and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
Complete your application on knightscope.bamboohr.com. The employer’s form will show what is required.
Already applied? Track this application
Job 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
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
Compensation and Benefits Base Salary: $180,000 to $210,000 (DOE) Equity: Stock options
- Location & working pattern
Sunnyvale, California, United States
Benefits: Medical, dental, vision, 401(k), paid time off Location Requirement: Full-time, on-site at Sunnyvale HQ
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
See how this role fits your experience
Add your resume to compare the role’s scope, tools and requirements with your experience.