MLOps Engineer

Staff MLOps Engineer

Company Description:
Drawing on nearly four centuries of collective experience across Wabtec, GE Transportation and Faiveley Transport, the company has unmatched digital expertise, technological innovation, and world‑class manufacturing and services, enabling the digital‑rail‑and‑transit ecosystems. Wabtec is focused on performance that drives progress, creating transportation solutions that move and improve the world. Wabtec has approximately 27,000 employees in facilities throughout the world. Visit: http://www.WabtecCorp.com.

Position Overview

We are seeking a Staff‑level MLOps Engineer to architect, build, and operationalize the deep learning platform for large‑scale computer vision systems. This role is ideal for someone who can work independently, define technical direction, and build end‑to‑end ML pipelines from the ground up.

You will be responsible for the full lifecycle of ML systems data ingestion, training, deployment, monitoring, observability, and ongoing operations while collaborating closely with deep learning researchers, software engineers, and product teams.
This Staff engineer will act as a technical authority, mentor other engineers, and establish engineering excellence across the org.

Remote Visual Inspection (RVI) systems enable high‑precision, non‑contact inspection of critical industrial components using advanced imaging, optics, and AI‑driven analytics. In this role, you will help shape the next generation of intelligent inspection capabilities by architecting the machine learning platform that powers automated defect detection and measurement in challenging environments. You will build the end‑to‑end infrastructure that enables large‑scale ingestion, training, deployment, and monitoring of computer vision models used in high‑speed visual inspection workflows. This position combines deep expertise in MLOps, cloud platforms, and computer vision systems to ensure that inspection models are reliable, scalable, and continuously improving ultimately enabling accurate, real‑time evaluation of assets using cutting‑edge camera and sensor technologies.

Responsibilities

MLOps Platform Ownership (Staff‑level)

• Define and own the overall MLOps architecture for deep learning systems across the organization.
• Design and implement end‑to‑end ML pipelines for data ingestion, training, validation, deployment, and monitoring.
• Build and maintain CI/CD pipelines for automated model training, evaluation, and deployment.
• Establish model serving infrastructure, including scalable and reliable real‑time or batch inference pipelines.
• Implement model monitoring, data drift detection, performance observability, and alerting frameworks.
• Ensure reliability, scalability, and reproducibility of ML workflows and experiments.
• Manage model versioning, artifact storage, and experiment tracking (MLflow, Kubeflow, TFX, etc.).
• Define and enforce ML specific CI/CD standards and operational best practices.

Data Engineering for ML

• Design and maintain a data aggregation and data ingestion solution for large‑scale vision datasets.
• Build data pipelines, feature stores, and dataset validation frameworks.
• Contribute to the development and improvement of the computer vision data lake and storage systems.

Computer Vision & Deep Learning

• Design, develop, and optimize CV models for detection, segmentation, classification, and tracking.
• Collaborate with algorithm and deep learning teams to transition R&D models into production‑grade pipelines.

Cloud & Infrastructure

• Work with cloud platforms (AWS, GCP, or Azure) to deploy scalable ML systems.
• Build training and inference solutions using Azure ML / AWS SageMaker / GCP Vertex AI.
• Implement containerized ML services using Docker and Kubernetes.

Cross‑Team Collaboration & Leadership

• Mentor junior engineers and guide teams as the technical authority for MLOps and ML lifecycle management.
• Collaborate closely with algorithm developers, CV engineers, data engineers, and platform teams.
• Champion engineering excellence, reliability, and automation.

Requirements

Core Technical Skills

• Bachelor’s/Master’s degree in Computer Science, Engineering, or related field.
• 7+ years of experience in MLOps, Computer Vision, and Python (staff‑level contribution expected).
• Strong understanding of ML workflow orchestration, lifecycle management, and platform design.
• Advanced Python skills and or proficiency in C++

Deep Learning & CV

• Hands‑on experience with PyTorch, TensorFlow, scikit‑learn.
• Strong experience in building and deploying production CV systems.

MLOps & Data

• Experience with MLflow, Kubeflow, TFX, DAG‑based workflow engines (Airflow, Prefect, etc.).
• Experience designing data ingestion pipelines, dataset management systems, and feature stores.
• Familiarity with vector DBs, search‑and‑retrieval systems, and document stores.

Cloud & Deployment

• Hands‑on experience with Azure ML, AWS SageMaker, or equivalent production ML platforms.
• Strong understanding of Docker, Kubernetes, GitLab CI/GitHub Actions.

Soft Skills

• Demonstrated technical leadership on complex ML systems.
• Excellent problem‑solving, communication, and collaboration skills.
• Ability to operate independently and drive architectural decisions.

What could you accomplish in a place that puts People First?

At Wabtec, it’s not just about a job - it’s about the impact you make. When our people come together, we’re Expanding the Possible by continuously improving what we do and how we do it - for our clients and each other.

If you’re ready to revolutionize how the world moves for future generations, Wabtec is the place for you.
 

Who are we?

Wabtec is a leading global provider of equipment, systems, digital solutions, and value-added services for the freight and transit rail sectors. Drawing on more than 150 years of experience, we are leading the way in safety, efficiency, reliability, innovation, and productivity. Whether it’s freight, transit, ports, logistics, mining, industrial, or marine, our expertise, technologies, and people together – are accelerating the future of transportation. With roots that date back to George Westinghouse, Thomas Edison, and Louis Faiveley, Wabtec has always built technologies and implemented solutions for a variety of sectors that are critical to meeting the needs of customers and governments alike.

Our global team of about 30,000 employees worldwide delivers performance that moves the world forward. We’re lifelong learners, obsessed with better. Learn more at www.WabtecCorp.com.

Culture powers us and the possibilities.

We believe the best ideas come from a mix of experiences and backgrounds. At Wabtec, we strive every day to create a place where everyone belongs. We’re building a culture where leadership, inclusion and your unique perspective fuel progress.

We’re proud to be an Equal Opportunity Employer. We welcome talent of all backgrounds, experiences, and identities, including race, gender, age, disability, veteran status and more.

Need accommodation? Just let us know - we’ve got you.