Machine Learning Operations Engineer

Swarmbotics AI • Phoenix, AZ

101d

About The Position

SwarmboticsAI is seeking a highly skilled MLOps Engineer to design, build, and maintain the machine learning infrastructure that powers our autonomous swarm systems. This engineer will be responsible for creating robust, scalable ML pipelines that support our perception team's cutting-edge computer vision and deep learning models. You'll ensure seamless model training, deployment, and monitoring across our fleet of UGVs. This engineer will work closely with our ML/Perception team and company leadership to scale our ML capabilities across the SwarmboticsAI product roadmap.

Requirements

• Minimum 2 years 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 (Kubeflow, MLflow, or similar)
• Proficiency in containerization (Docker, Kubernetes) and cloud platforms (AWS, GCP, Azure)
• Strong Python programming and Linux system administration skills
• Experience with model serving frameworks (TensorRT, ONNX Runtime, TorchServe)
• Knowledge of data versioning and experiment tracking (Weights & Biases, Neptune, or similar)
• Experience with monitoring and logging systems (Prometheus, Grafana, ELK stack)
• Strong organization and communication to work well across teams in a fast-paced startup environment
• Comfort working in the high-paced, fluid environment of a tech startup
• Excitement about contributing to the defense of the United States and its allies
• Must be eligible to work on export-controlled projects.
• Ability to relocate to Phoenix, AZ area

Nice To Haves

• Masters degree in computer science, engineering, or related field
• Experience with edge AI deployment and embedded systems optimization
• Prior robotics or autonomous vehicle MLOps experience
• Experience with real-time data streaming (Kafka, RabbitMQ)
• Knowledge of security and compliance requirements for defense applications
• Experience with multi-modal sensor data processing and fusion
• Familiarity with ROS and robotics software stacks

Responsibilities

• Design and implement end-to-end ML pipelines for training, validation, and deployment of perception models
• Develop robust data management systems for large-scale sensor data (cameras, LiDAR, IMU) collected from field operations
• Implement model monitoring, A/B testing, and performance tracking systems for deployed models
• Build CI/CD pipelines for model versioning, testing, and deployment to vehicle fleets
• Design distributed computing solutions for large-scale data processing and model training
• Create tools for data annotation, model evaluation, and performance visualization
• Work collaboratively with perception engineers, robotics teams, and field operations

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 1-10 employees