Computer Vision Engineer

Pratt & Whitney, an RTX business, is a world leader in the design, manufacture and service of aircraft engines and auxiliary power units for commercial, military and business aircraft. Through industry-leading businesses – Collins Aerospace, Pratt & Whitney, and Raytheon – RTX pushes the limits of technology and science to redefine how we connect and protect our world.
We are advancing aviation, engineering integrated defense systems, and developing next-generation technology solutions and manufacturing to help global customers address their most critical challenges. Make a difference with a career at Pratt & Whitney.

This is an exciting opportunity as a Computer Vision Engineer, supporting the continued growth and evolution of Pratt & Whitney's AI-powered digital inspection solutions. In this role, you will design, deploy, and maintain advanced machine learning models and computer vision pipelines that power our cutting-edge jet engine inspection platform across the global aftermarket network. If you are passionate about transforming complex engineering challenges into intelligent, high-performance predictive features through data-driven development and emerging AI technologies, this may be the opportunity you've been looking for.

You will partner cross-functionally with software, product, and aviation domain teams to integrate novel computer vision capabilities into production software. This is a critical role supporting the continued growth of Pratt & Whitney's digital product portfolio by driving the end-to-end model lifecycle, building robust data feedback loops, and delivering exceptional customer experiences through user-centered AI features and continuous innovation.

• →Work with state-of-the-art AI products that solve real-world customer problems.
• →Work in an international environment, with an energetic and enthusiastic team that is capable, takes ownership and is hungry for growth and knowledge.
• →Collaborate closely with CV engineers, software engineers and product team to deliver AI-assisted engine inspection solutions for aviation professionals globally.
• →Take part in driving the model lifecycle cadence of data review, model training, evaluation, selection, and production release.
• →Build data feedback loops to identify and ingest high-value operational data and edge cases back into retraining pipelines.
• →Prototype and benchmark novel computer vision and predictive features for AI-assisted inspection products.
• →Translate research concepts into clean, modular, production-grade code.
• →Partner cross-functionally with software, product and aviation domain teams to integrate useful intelligent features into production software.

• You, be yourself, we value the diversity you bring to the team.
• B.S. or M.S. in Computer Science, Data Science or a related quantitative field (or equivalent hands-on industry experience).
• 5+ years of professional experience developing and deploying machine learning and computer vision models in production environments.
• You are independent, proactive, eager to learn, and committed to continuously expanding your knowledge within AI development.
• You have strong problem-solving abilities and a proactive mindset to identify and address challenges to provide our customers with an outstanding experience.
• You are a team player who actively contributes ideas, gives and receives feedback regularly, and communicates early about issues, uncertainties, risks, and opportunities.
• You are familiar with an Agile/Kanban environment and embody an agile mindset and lean principles.
• Solid understanding of modern computer vision architectures (object detection, semantic/instance segmentation, feature matching) using PyTorch.
• Strong Python software engineering skills (OOP, design patterns, unit/integration testing, standard data structures) with a focus on code maintainability and scalability.
• Practical experience with model versioning, tracking, and serving frameworks (e.g. Docker, ONNX Runtime, DVC, MLflow, Weights & Biases).
• You have effective time management and organizational skills to meet deadlines.

• Prior experience in aviation, aerospace, non-destructive testing (NDT), spatial inspection, or heavy industrial automation.
• Familiarity with 3D data representations (point clouds, meshes, CAD formats) and libraries like Open3D, PyTorch3D, or Gaussian Splatting.
• Proven experience working with complex datasets beyond standalone images; specifically, fusing vision data with sensor time-series, spatial data, or 3D models.
• Background in time-series forecasting or anomaly detection applied to sensor streams for predictive failure analysis.
• Experience optimizing deep learning models for edge compute or low-latency environments (e.g., TensorRT, OpenVINO, CUDA optimization).

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