Machine Learning Operations Engineer

Who is Recruiting from Scratch

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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.

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