Senior AI – Computer Vision Engineer
Oxy, Houston, TX, United States
Senior AI – Computer Vision Engineer (Hybrid/On-site) – Houston, TX
Job Overview
We are looking for an experienced and innovative Senior AI – Computer Vision Engineer to join the AI Center of Excellence (ACE) group based in Houston, TX. This individual contributor role focuses on designing, developing, and deploying production‑grade computer vision solutions across Oxy, supporting a wide range of industrial, operational, and subsurface use cases.
Essential Job Responsibilities
Design and select appropriate computer vision model architectures for classification, detection, segmentation, and object tracking.
Work with classification architectures such as ResNet, VGG, EfficientNet, and MobileNet, and segmentation architectures such as U‑Net.
Build, train, fine‑tune, and optimize models using Ultralytics YOLO for object detection and segmentation (required).
Develop deep learning models using PyTorch and TensorFlow.
Lead research and development (R&D) efforts to evaluate, prototype, and adopt state‑of‑the‑art (SOTA) computer vision models and techniques where they provide business or operational value.
Stay current with advances in computer vision research, including new architectures, training methods, and foundation models, and translate relevant innovations into practical solutions.
Leverage Hugging Face for pretrained backbones, model assets, and rapid experimentation.
Apply Vision‑Language Models (VLMs) to multimodal computer vision workflows (e.g., OCR, image‑to‑text, prompt‑driven visual understanding).
Design, manage, and continuously improve image and video labeling workflows, using Roboflow or similar annotation tools.
Deliver computer vision models for surface and downhole image analysis, including lithology, facies, and textural interpretation.
Optimize computationally heavy training and inference workloads, including GPU utilization, memory efficiency, and throughput/latency tradeoffs.
Work with GPU‑accelerated environments (CUDA‑enabled frameworks) and AWS‑based ML infrastructure, including Amazon SageMaker when appropriate.
Collaborate closely with cross‑functional teams (AI platform, software engineering, domain experts) and mentor junior engineers.
Communicate technical findings, experimental results, and recommendations clearly through presentations, demos, and written documentation.
Qualifications
PhD in Computer Science or a related technical field preferred, or equivalent industry experience building production computer vision systems.
6+ years of hands‑on experience in computer vision or applied deep learning.
Excellent Python skills (required), including writing clean, efficient, production‑ready code.
Strong experience with PyTorch, TensorFlow, CNN‑based architectures, transformers, and Vision‑Language Models.
Ultralytics YOLO experience required, including training and tuning on real‑world datasets.
Practical familiarity with Hugging Face and Roboflow.
Experience working with GPU‑accelerated workloads and CUDA‑enabled deep learning frameworks.
Experience developing or running ML workloads on AWS, including Amazon SageMaker and GPU instances.
Strong experience working in Linux environments.
Excellent teamwork, communication, and presentation skills, with the ability to explain complex technical concepts to both technical and non‑technical audiences.
Demonstrated contributions to computer vision research, including peer‑reviewed publications, conference papers, or equivalent applied research output.
Equal Opportunity Statement
All qualified applicants will receive consideration for employment without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by federal, state, or local law.
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Job Overview
We are looking for an experienced and innovative Senior AI – Computer Vision Engineer to join the AI Center of Excellence (ACE) group based in Houston, TX. This individual contributor role focuses on designing, developing, and deploying production‑grade computer vision solutions across Oxy, supporting a wide range of industrial, operational, and subsurface use cases.
Essential Job Responsibilities
Design and select appropriate computer vision model architectures for classification, detection, segmentation, and object tracking.
Work with classification architectures such as ResNet, VGG, EfficientNet, and MobileNet, and segmentation architectures such as U‑Net.
Build, train, fine‑tune, and optimize models using Ultralytics YOLO for object detection and segmentation (required).
Develop deep learning models using PyTorch and TensorFlow.
Lead research and development (R&D) efforts to evaluate, prototype, and adopt state‑of‑the‑art (SOTA) computer vision models and techniques where they provide business or operational value.
Stay current with advances in computer vision research, including new architectures, training methods, and foundation models, and translate relevant innovations into practical solutions.
Leverage Hugging Face for pretrained backbones, model assets, and rapid experimentation.
Apply Vision‑Language Models (VLMs) to multimodal computer vision workflows (e.g., OCR, image‑to‑text, prompt‑driven visual understanding).
Design, manage, and continuously improve image and video labeling workflows, using Roboflow or similar annotation tools.
Deliver computer vision models for surface and downhole image analysis, including lithology, facies, and textural interpretation.
Optimize computationally heavy training and inference workloads, including GPU utilization, memory efficiency, and throughput/latency tradeoffs.
Work with GPU‑accelerated environments (CUDA‑enabled frameworks) and AWS‑based ML infrastructure, including Amazon SageMaker when appropriate.
Collaborate closely with cross‑functional teams (AI platform, software engineering, domain experts) and mentor junior engineers.
Communicate technical findings, experimental results, and recommendations clearly through presentations, demos, and written documentation.
Qualifications
PhD in Computer Science or a related technical field preferred, or equivalent industry experience building production computer vision systems.
6+ years of hands‑on experience in computer vision or applied deep learning.
Excellent Python skills (required), including writing clean, efficient, production‑ready code.
Strong experience with PyTorch, TensorFlow, CNN‑based architectures, transformers, and Vision‑Language Models.
Ultralytics YOLO experience required, including training and tuning on real‑world datasets.
Practical familiarity with Hugging Face and Roboflow.
Experience working with GPU‑accelerated workloads and CUDA‑enabled deep learning frameworks.
Experience developing or running ML workloads on AWS, including Amazon SageMaker and GPU instances.
Strong experience working in Linux environments.
Excellent teamwork, communication, and presentation skills, with the ability to explain complex technical concepts to both technical and non‑technical audiences.
Demonstrated contributions to computer vision research, including peer‑reviewed publications, conference papers, or equivalent applied research output.
Equal Opportunity Statement
All qualified applicants will receive consideration for employment without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by federal, state, or local law.
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