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Video Labelling Jobs in Conroe, TX (NOW HIRING)

Senior AI - Computer Vision Engineer

Houston, TX · On-site

$117K - $154.20K/yr

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 ...

Senior AI - Computer Vision Engineer

Houston, TX · On-site

$99.80K - $137K/yr

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 ...

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 ...

... labels (e.g. identifying speaker), ensure compliance with standard formats. * Prepare the video for presentation, which may include formatting for court use, making backup copies, encoding ...

... labels (e.g. identifying speaker), ensure compliance with standard formats. * Prepare the video for presentation, which may include formatting for court use, making backup copies, encoding ...

... labels (e.g. identifying speaker), ensure compliance with standard formats. * Prepare the video for presentation, which may include formatting for court use, making backup copies, encoding ...

Facility Warehouser

Houston, TX · On-site

$16 - $20/hr

Receive and process warehouse stock products (pick, unload, label, store) * Check incoming ... While you can complete this video interview on your own schedule, we ask that this step be ...

... label video content in proper manner for storage and future use • Be on-site at junior/professional golf events throughout the season • This position will be attending 1-2 events per week which ...

Video Labelling information

See Conroe, TX salary details

$13

$21

$34

How much do video labelling jobs pay per hour?

As of Jun 1, 2026, the average hourly pay for video labelling in Conroe, TX is $21.77, according to ZipRecruiter salary data. Most workers in this role earn between $16.44 and $24.90 per hour, depending on experience, location, and employer.

What is a Video Labelling job?

A Video Labelling job involves annotating or tagging objects, actions, or events in video footage to train machine learning models. This process helps AI systems recognize and interpret visual data accurately. Tasks may include drawing bounding boxes, classifying scenes, or adding timestamps for specific events. Video labelling is commonly used in industries like autonomous driving, security surveillance, and content moderation.

What are the key skills and qualifications needed to thrive in the Video Labelling position, and why are they important?

To thrive as a Video Labelling professional, you should have excellent attention to detail, basic computer proficiency, and familiarity with visual content analysis. Knowledge of annotation platforms, video editing software, or AI training tools is often required, and experience with data labelling systems can be beneficial. Strong communication, reliability, and the ability to follow detailed guidelines are important soft skills for this role. These abilities ensure high-quality, consistent data annotation that directly supports machine learning and computer vision projects.

What does a typical day look like for someone working in Video Labelling?

A typical day in Video Labelling involves reviewing video footage, identifying and annotating specific objects or events according to project guidelines, and entering this data into specialized software tools. Team members often collaborate with data scientists, engineers, or quality assurance leads to ensure accuracy and consistency in the annotations. Depending on the project and employer, you may work independently or as part of a larger team, sometimes with set quotas or deadlines. This work is crucial for developing and refining AI and machine learning models, making attention to detail and adherence to standards especially important. Over time, experienced video labelling professionals may progress to quality assurance roles or team leads overseeing larger annotation projects.
What are popular job titles related to Video Labelling jobs in Conroe, TX? For Video Labelling jobs in Conroe, TX, the most frequently searched job titles are:
What cities near Conroe, TX are hiring for Video Labelling jobs? Cities near Conroe, TX with the most Video Labelling job openings:
Infographic showing various Video Labelling job openings in Conroe, TX as of May 2026, with employment types broken down into 74% Full Time, 15% Part Time, and 11% Contract. Highlights an 100% In-person job distribution, with an average salary of $45,278 per year, or $21.8 per hour.
Senior AI - Computer Vision Engineer

Senior AI - Computer Vision Engineer

Occidental Petroleum Corporation

Houston, TX • On-site

$99.80K - $137K/yr

Other

Posted 24 days ago


Occidental Petroleum rating

9.0

Company rating: 9.0 out of 10

Based on 18 frontline employees who took The Breakroom Quiz

3rd of 74 rated oil and gas companies


Job description

Senior AI – Computer Vision Engineer

Oxy produces, markets and transports oil and natural gas to maximize value and provide resources fundamental to life. The company leverages its global leadership in carbon management to advance lower-carbon technologies and products. Headquartered in Houston, Oxy primarily operates in the United States, Middle East and North Africa.

Oxy strives to attract and retain talented employees by investing in their professional development and providing rewarding opportunities for personal growth. Our goal is to meet the highest employer standards by ensuring the health and safety of our employees, protecting the environment and positively impacting our communities where we do business.

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
  • Master's Degree in Computer Science or a related technical field required.
  • 6+ years of hands‑on experience in computer vision or applied deep learning. An equivalent combination of relevant education and experience will be considered.
  • 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

Occidental does not offer sponsorship of employment-based nonimmigrant visa petitions for this role.

Recruitment Fraud It has come to our attention various individuals and/or organizations are contacting people falsely pretending to recruit on behalf of Oxy. Please be aware that these recruiting scams and communications do not originate nor are they associated with our recruitment process. All Oxy job postings and offers will require a completed application through our company website. Oxy does not charge a fee at any stage of the recruiting process. We will never:• Ask you to pay for applications, interviews, meetings, processing, training or for any other fees • Use recruiting or placement agencies that charge candidates an advance fee of any kind or • Request personal information such as passport and bank account details at an early stage of our recruitment process. We recommend against responding to unsolicited business propositions or offers from people you don't know. Do not disclose your personal or financial details. If you believe you have been the victim of a recruiting scam, please contact your local police department.

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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