H-1B Visa Computer Vision Engineer Jobs
Computer Vision Engineer roles qualify as H-1B specialty occupations under the computer science and engineering SOC codes, making them strong candidates for employer sponsorship. Tech, autonomous vehicles, robotics, and medical imaging companies file LCAs regularly for this title. No lottery anxiety: your skills put you in high demand.
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INTRODUCTION
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
- 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
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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Get Access To All JobsTips for Finding H-1B Visa Sponsorship as a Computer Vision Engineer
Verify your role meets specialty occupation
Computer Vision Engineer must require a bachelor's degree or higher in computer science, electrical engineering, or a directly related field. If your job description says 'preferred' instead of 'required,' the H-1B petition is vulnerable to an RFE. Push your employer to tighten the language before filing.
Check prevailing wage before accepting offers
Use the OFLC Wage Search to look up the DOL prevailing wage for your SOC code and work location before you negotiate. Your offer must meet or exceed that figure for the LCA to be certified, so knowing the floor protects you from underpaid petitions.
Target employers with active LCA filing history
Search Migrate Mate to filter Computer Vision Engineer roles by employers who have filed H-1B LCAs for this specific occupation. Employers with consistent filing history have an established process and are less likely to stall or withdraw after the lottery.
Document your degree field equivalency early
If your degree is in physics, mathematics, or a non-CS discipline, get a credential evaluation from a NACES-approved organization before your employer files. USCIS scrutinizes degree-to-role fit closely for engineering petitions, and a missing equivalency letter is a common RFE trigger.
Ask about premium processing before the lottery
Employers can upgrade an approved H-1B petition to premium processing through USCIS, which guarantees a 15-business-day adjudication. For Computer Vision roles with project start dates tied to product cycles, confirm whether your employer will elect premium so delays don't push your start date past October 1.
Reference O*NET to strengthen specialty occupation evidence
The O*NET occupation profile for Computer Vision and related engineering roles lists the education and knowledge requirements USCIS uses to evaluate specialty occupation claims. Share the relevant O*NET data with your employer's immigration counsel to support the petition's occupational evidence section.
Computer Vision Engineer jobs are hiring across the US. Find yours.
Find Computer Vision Engineer JobsComputer Vision Engineer H-1B Visa: Frequently Asked Questions
Does a Computer Vision Engineer role qualify as an H-1B specialty occupation?
Yes. Computer Vision Engineer falls under SOC codes tied to software developers and electrical and electronics engineers, both of which USCIS consistently recognizes as specialty occupations requiring at least a bachelor's degree in a directly related field. The key is that your job description must specify the degree as a requirement, not a preference. Roles at the intersection of machine learning and imaging are well-established in USCIS adjudication history.
Which industries sponsor H-1B visas most often for Computer Vision Engineers?
Autonomous vehicle companies, robotics manufacturers, medical imaging firms, defense contractors, and large technology companies are the most consistent H-1B sponsors for Computer Vision Engineers. Startups in AR and VR also file regularly. You can browse verified LCA filing history for this role by employer on Migrate Mate to see which companies have active sponsorship patterns before you apply.
What happens to my H-1B status if my Computer Vision project is canceled mid-petition?
If your employer withdraws the H-1B petition after USCIS approval but before your start date, you retain a 60-day grace period to find a new sponsor and file an H-1B transfer. If the petition is withdrawn while you're already working in H-1B status, the same 60-day rule applies. Document your last day of employment and act quickly, because the grace period doesn't pause.
Can I transfer my H-1B to a new employer if my Computer Vision role changes significantly?
Yes, but the new employer must file an H-1B transfer petition before your current status expires, and the new role must still qualify as a specialty occupation. If the job duties shift substantially, for example from pure research to a product management hybrid, USCIS may scrutinize whether the degree requirement still holds. A transfer is typically straightforward when the new role maps cleanly to the same SOC code.
Does a master's degree in computer science improve my H-1B approval odds for this role?
A master's degree strengthens your petition in two ways. It eliminates the degree-to-role fit scrutiny that bachelor's-level applicants sometimes face, and it makes you eligible for the master's cap, which historically has higher selection rates than the regular cap. For competitive Computer Vision specializations like 3D reconstruction or deep learning, a graduate degree also supports higher prevailing wage levels in the DOL's four-tier structure.
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