Senior Software Engineer, MLOps

FieldAI is transforming how robots interact with the real world by building reliable, risk-aware AI systems for complex challenges in robotics. They are seeking a skilled Senior MLOps Engineer to design and maintain the infrastructure supporting machine learning systems in robotics applications, collaborating with various engineering teams to ensure efficient deployment and monitoring of ML models.

Responsibilities

Design, build, and maintain GPU based infrastructure for machine learning pipelines, including data processing, training, evaluation, inference and deployment workflows

Collaborate closely with robotics teams to implement model serving infrastructure for edge/robot deployment

Build tools and automation to support reproducible experiments, model versioning, and dataset management

Deploy and manage ML services and inference pipelines using containerized environments for efficient scaling and scheduling of heterogeneous compute resources

Monitor model performance and system reliability across development and production environments

Improve the efficiency, scalability, and reliability of ML workflows and infrastructure

Work with cross-functional engineering teams to integrate ML components into robotics software systems

Preferred

Experience deploying and operating ML systems for robotics or real-world physical systems

Experience with scaling AI, ML, and inference workloads on Kubernetes

Exposure to ROS-based robotics data formats and pipelines (rosbags, point clouds)

Experience with experiment tracking, model versioning, or dataset versioning tools

Experience optimizing ML pipelines for large-scale training and data processing

Experience working closely with research or applied machine learning teams

ML systems deployment

AI scaling on Kubernetes

ROS data formats

Experiment tracking tools

Model versioning tools

Dataset versioning tools

Optimizing ML pipelines

Large-scale data processing

Collaboration with ML teams

Benefits

We are open to exploring a hybrid or remote option

Company

General-purpose robotics AI for unstructured physical environments

Irvine, California, USA

https://www.fieldai.com/

Founded in 2023

201-500 employees

Qualifications

Bachelor's degree in Computer Science, Engineering, or a related field (or equivalent work experience)

3-7 years of experience in MLOps, machine learning infrastructure, or related engineering roles

Strong programming skills in Python or similar languages

Experience building and maintaining machine learning pipelines

Hands-on experience with cloud and cloud-native tools such as AWS (SageMaker, S3, or similar cloud ML services), Kubernetes etc

Solid understanding of Linux systems and distributed computing environments

Experience with GPU workload scheduling and orchestration across multi-region cloud environments

Excellent problem-solving skills and the ability to work collaboratively in a team environment

Experience deploying and operating ML systems for robotics or real-world physical systems

Experience with scaling AI, ML, and inference workloads on Kubernetes

Exposure to ROS-based robotics data formats and pipelines (rosbags, point clouds)

Experience with experiment tracking, model versioning, or dataset versioning tools

Experience optimizing ML pipelines for large-scale training and data processing

Experience working closely with research or applied machine learning teams

3-7 years of experience in MLOps, machine learning infrastructure, or related engineering roles.

Required skills

MLOps, Machine learning infrastructure, Python, AWS SageMaker, AWS S3, Kubernetes, Linux systems, Distributed computing, GPU workload scheduling, Containerization, Model versioning, Dataset management, Experiment tracking

Experience

3-7 years