Insight Recruitment
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Base pay range
$140,000.00/yr - $180,000.00/yr Overview
ML Ops Engineer @ AI Robotics ScaleUp - Up to $180k + Equity Join a cutting-edge startup at the intersection of
AI, robotics, and national security
— developing
next-gen autonomous systems
that combine advanced machine learning with edge computing to enable coordinated, intelligent behavior across fleets of unmanned ground vehicles. The Opportunity We’re seeking an
MLOps Engineer
to help design, build, and scale the infrastructure that powers our autonomous swarm systems. You’ll play a key role in creating the ML backbone that supports our perception and decision-making models — ensuring fast, reliable, and secure deployment of intelligence across an expanding fleet of AI-driven vehicles. This is a rare opportunity to work hands-on with
robotics, deep learning, and real-world deployment
— building pipelines that don’t just run in the cloud, but
power machines in the field . What You’ll Do
Design and maintain
end-to-end ML pipelines
for model training, validation, and deployment Build scalable data systems to handle
massive sensor inputs
(cameras, LiDAR, IMU) from real-world operations Implement
model monitoring, A/B testing, and automated feedback loops
for continuous performance improvement Develop
CI/CD workflows
for model versioning, testing, and fleet deployment Architect
distributed computing solutions
for high-volume data processing and large-scale model training 2+ years of experience in
MLOps, DevOps, or ML infrastructure Experience with
pipeline orchestration tools
(e.g., Kubeflow, MLflow) Proficiency with
Docker, Kubernetes , and
cloud platforms
(AWS, GCP, or Azure) Skilled in
Python
and
Linux system administration Familiar with
model serving frameworks
(TensorRT, ONNX Runtime, TorchServe) Experience with
monitoring and logging
(Prometheus, Grafana, ELK stack) Strong communication and organization skills — thrives in a
fast-paced, collaborative startup
environment Security Clearable Willing to
relocate to the Phoenix, AZ area Why Join Us
Be part of a team building
mission-critical AI systems
that make a real-world impact Work alongside
pioneers in robotics and AI Tackle
complex, frontier-scale challenges
in distributed ML and autonomy Shape the future of how
intelligent machines collaborate and operate
in the field Responsibilities & Qualifications
2+ years of experience in
MLOps, DevOps, or ML infrastructure Proficiency with
Python
and
Linux
system administration Experience with
Docker, Kubernetes
and
cloud platforms
(AWS, GCP, Azure) Experience with
CI/CD
pipelines and
model versioning Employment details
Employment type:
Full-time Seniority level:
Mid-Senior level Job function:
Engineering and Information Technology Note: This posting excludes irrelevant boilerplate job board notices. The content above reflects the core role, responsibilities, and requirements without extraneous listings.
#J-18808-Ljbffr
$140,000.00/yr - $180,000.00/yr Overview
ML Ops Engineer @ AI Robotics ScaleUp - Up to $180k + Equity Join a cutting-edge startup at the intersection of
AI, robotics, and national security
— developing
next-gen autonomous systems
that combine advanced machine learning with edge computing to enable coordinated, intelligent behavior across fleets of unmanned ground vehicles. The Opportunity We’re seeking an
MLOps Engineer
to help design, build, and scale the infrastructure that powers our autonomous swarm systems. You’ll play a key role in creating the ML backbone that supports our perception and decision-making models — ensuring fast, reliable, and secure deployment of intelligence across an expanding fleet of AI-driven vehicles. This is a rare opportunity to work hands-on with
robotics, deep learning, and real-world deployment
— building pipelines that don’t just run in the cloud, but
power machines in the field . What You’ll Do
Design and maintain
end-to-end ML pipelines
for model training, validation, and deployment Build scalable data systems to handle
massive sensor inputs
(cameras, LiDAR, IMU) from real-world operations Implement
model monitoring, A/B testing, and automated feedback loops
for continuous performance improvement Develop
CI/CD workflows
for model versioning, testing, and fleet deployment Architect
distributed computing solutions
for high-volume data processing and large-scale model training 2+ years of experience in
MLOps, DevOps, or ML infrastructure Experience with
pipeline orchestration tools
(e.g., Kubeflow, MLflow) Proficiency with
Docker, Kubernetes , and
cloud platforms
(AWS, GCP, or Azure) Skilled in
Python
and
Linux system administration Familiar with
model serving frameworks
(TensorRT, ONNX Runtime, TorchServe) Experience with
monitoring and logging
(Prometheus, Grafana, ELK stack) Strong communication and organization skills — thrives in a
fast-paced, collaborative startup
environment Security Clearable Willing to
relocate to the Phoenix, AZ area Why Join Us
Be part of a team building
mission-critical AI systems
that make a real-world impact Work alongside
pioneers in robotics and AI Tackle
complex, frontier-scale challenges
in distributed ML and autonomy Shape the future of how
intelligent machines collaborate and operate
in the field Responsibilities & Qualifications
2+ years of experience in
MLOps, DevOps, or ML infrastructure Proficiency with
Python
and
Linux
system administration Experience with
Docker, Kubernetes
and
cloud platforms
(AWS, GCP, Azure) Experience with
CI/CD
pipelines and
model versioning Employment details
Employment type:
Full-time Seniority level:
Mid-Senior level Job function:
Engineering and Information Technology Note: This posting excludes irrelevant boilerplate job board notices. The content above reflects the core role, responsibilities, and requirements without extraneous listings.
#J-18808-Ljbffr