Recruiting from Scratch
Machine Learning Operations Engineer
Recruiting from Scratch, Phoenix, Arizona, United States, 85003
Who is Recruiting from Scratch:
Recruiting from Scratch is a specialized talent firm dedicated to helping companies build exceptional teams. We partner closely with our clients to deeply understand their needs, then connect them with top-tier candidates who are not only highly skilled but also the right fit for the company's culture and vision. Our mission is simple: place the best people in the right roles to drive long-term success for both clients and candidates. https://www.recruitingfromscratch.com/
Title of Role : Machine Learning Operations Engineer Location : Phoenix, AZ (On-site) Company Stage of Funding : Early-Stage, Venture-Backed Office Type : On-site, Full-Time Salary : Competitive + Equity Company Description
We're representing a
defense technology company
building next-generation
autonomous swarm systems
for unmanned ground vehicles (UGVs). The company is applying cutting-edge
machine learning and edge AI
to deliver low-cost coordinated robotic fleets capable of executing complex missions across multiple domains.The leadership team brings decades of experience in self-driving vehicles, aerospace, and defense, and the company is rapidly scaling its engineering team in Phoenix, AZ to meet growing demand. What You Will Do
As a
Machine Learning Operations Engineer , you'll design, build, and maintain the ML infrastructure that powers perception and autonomy across vehicle swarms. You will:
Design and implement
end-to-end ML pipelines
for training, validation, and deployment of perception models. Build robust
data management systems
for large-scale sensor data (cameras, LiDAR, IMU) from field operations. Implement
model monitoring, A/B testing, and performance tracking
systems for deployed models. Develop CI/CD pipelines for
model versioning, testing, and deployment
to fleets of autonomous UGVs. Create distributed computing solutions for
large-scale data processing and model training . Build internal tools for
data annotation, evaluation, and performance visualization . Collaborate with perception engineers, robotics teams, and field ops to ensure seamless deployment. Ideal Background
2+ years of industry experience in
MLOps, DevOps, or ML infrastructure . Bachelor's degree in computer science, engineering, or related field. Strong experience with ML pipeline orchestration tools (e.g.,
Kubeflow, MLflow ). Proficiency with
Docker, Kubernetes , and cloud platforms (AWS, GCP, or Azure). Strong
Python programming
and
Linux system administration
skills. Experience with
model serving frameworks
(TensorRT, ONNX Runtime, TorchServe). Familiarity with data versioning and experiment tracking tools (e.g.,
Weights & Biases, Neptune ). Experience with monitoring and logging systems ( Prometheus, Grafana, ELK stack ). Strong organizational and communication skills; thrives in a
fast-paced startup environment . Eligible to work on
export-controlled projects
and willing to
relocate to Phoenix, AZ . Compensation and Benefits
Salary : Competitive (commensurate with experience) Equity : Meaningful early-stage ownership stake Work Setup : On-site in Phoenix, AZ (relocation assistance available) Other Benefits :
Direct ownership of core ML infrastructure powering real-world autonomy Opportunity to work across defense, robotics, and swarm AI systems Mission-driven, collaborative environment with leadership experienced in frontier robotics
This role is ideal for engineers passionate about scaling ML infrastructure, deploying cutting-edge models in the field, and building the backbone for autonomous swarm robotics in a fast-moving defense technology company.
Salary Range: $160,000-$200,000 base. https://www.recruitingfromscratch.com/
Recruiting from Scratch is a specialized talent firm dedicated to helping companies build exceptional teams. We partner closely with our clients to deeply understand their needs, then connect them with top-tier candidates who are not only highly skilled but also the right fit for the company's culture and vision. Our mission is simple: place the best people in the right roles to drive long-term success for both clients and candidates. https://www.recruitingfromscratch.com/
Title of Role : Machine Learning Operations Engineer Location : Phoenix, AZ (On-site) Company Stage of Funding : Early-Stage, Venture-Backed Office Type : On-site, Full-Time Salary : Competitive + Equity Company Description
We're representing a
defense technology company
building next-generation
autonomous swarm systems
for unmanned ground vehicles (UGVs). The company is applying cutting-edge
machine learning and edge AI
to deliver low-cost coordinated robotic fleets capable of executing complex missions across multiple domains.The leadership team brings decades of experience in self-driving vehicles, aerospace, and defense, and the company is rapidly scaling its engineering team in Phoenix, AZ to meet growing demand. What You Will Do
As a
Machine Learning Operations Engineer , you'll design, build, and maintain the ML infrastructure that powers perception and autonomy across vehicle swarms. You will:
Design and implement
end-to-end ML pipelines
for training, validation, and deployment of perception models. Build robust
data management systems
for large-scale sensor data (cameras, LiDAR, IMU) from field operations. Implement
model monitoring, A/B testing, and performance tracking
systems for deployed models. Develop CI/CD pipelines for
model versioning, testing, and deployment
to fleets of autonomous UGVs. Create distributed computing solutions for
large-scale data processing and model training . Build internal tools for
data annotation, evaluation, and performance visualization . Collaborate with perception engineers, robotics teams, and field ops to ensure seamless deployment. Ideal Background
2+ years of industry experience in
MLOps, DevOps, or ML infrastructure . Bachelor's degree in computer science, engineering, or related field. Strong experience with ML pipeline orchestration tools (e.g.,
Kubeflow, MLflow ). Proficiency with
Docker, Kubernetes , and cloud platforms (AWS, GCP, or Azure). Strong
Python programming
and
Linux system administration
skills. Experience with
model serving frameworks
(TensorRT, ONNX Runtime, TorchServe). Familiarity with data versioning and experiment tracking tools (e.g.,
Weights & Biases, Neptune ). Experience with monitoring and logging systems ( Prometheus, Grafana, ELK stack ). Strong organizational and communication skills; thrives in a
fast-paced startup environment . Eligible to work on
export-controlled projects
and willing to
relocate to Phoenix, AZ . Compensation and Benefits
Salary : Competitive (commensurate with experience) Equity : Meaningful early-stage ownership stake Work Setup : On-site in Phoenix, AZ (relocation assistance available) Other Benefits :
Direct ownership of core ML infrastructure powering real-world autonomy Opportunity to work across defense, robotics, and swarm AI systems Mission-driven, collaborative environment with leadership experienced in frontier robotics
This role is ideal for engineers passionate about scaling ML infrastructure, deploying cutting-edge models in the field, and building the backbone for autonomous swarm robotics in a fast-moving defense technology company.
Salary Range: $160,000-$200,000 base. https://www.recruitingfromscratch.com/