OPT Computer Vision Engineer Jobs
Computer Vision Engineer roles are among the most OPT-friendly in tech, with strong demand from autonomous vehicle, robotics, and defense companies that regularly sponsor H-1B visa and O-1 visas. Most positions require a master's or PhD in computer science or electrical engineering, which aligns well with STEM OPT's 24-month extension.
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INTRODUCTION
At Elanco (NYSE: ELAN) – it all starts with animals!
As a global leader in animal health, we are dedicated to innovation and delivering products and services to prevent and treat disease in farm animals and pets. At Elanco, we are driven by our vision of Food and Companionship Enriching Life and our purpose – all to Go Beyond for Animals, Customers, Society and Our People.
At Elanco, we pride ourselves on fostering a diverse and inclusive work environment. We believe that diversity is the driving force behind innovation, creativity, and overall business success. Here, you’ll be part of a company that values and champions new ways of thinking, work with dynamic individuals, and acquire new skills and experiences that will propel your career to new heights.
Making animals’ lives better makes life better – join our team today!
ROLE AND RESPONSIBILITIES
Your Role: Machine Learning & Computer Vision Scientist – R&D (Junior/Associate)
As the Machine Learning & Computer Vision Scientist (Junior/Associate), you will help drive Elanco’s R&D innovation by implementing and refining ML and computer-vision models that support faster, better-informed decisions. You will work closely with senior scientists and R&D stakeholders to turn proprietary molecular, in vitro, imaging, and digital endpoint data into predictive and classification models for target identification, molecular optimization, ADMET, and digital biomarkers in animal health.
Your Responsibilities:
- Implement and refine ML/CV models under guidance, developing, training, and tuning models on R&D datasets (molecular, in vitro, imaging, behavioral) in collaboration with senior scientists to align with scientific objectives.
- Prepare and manage datasets for modeling by cleaning, transforming, and merging data from multiple scientific sources, running exploratory analyses, and contributing to feature engineering and clear dataset documentation.
- Support data collection, annotation, and synthetic data work by helping improve capture and labeling workflows for images, video, and assay data, assisting with annotation guidelines, and evaluating synthetic data and augmentation to improve sparse datasets and model robustness.
- Assist with model evaluation and reporting by contributing to train/validation/test design, applying appropriate metrics and error analyses, and documenting methods, assumptions, limitations, and results for review and reuse.
- Collaborate and grow ML/CV expertise by joining cross-functional project meetings, sharing learnings through short demos or presentations, and actively building knowledge in drug discovery, development, and ML/CV techniques.
BASIC QUALIFICATIONS
What You Need to Succeed (minimum qualifications):
- Education: Master’s degree in a quantitative field (e.g., Data Science, Engineering, Mathematics, Physics, Statistics, Bioinformatics)
- Required Experience: Early applied ML/CV experience: 0–3 years applying ML and/or computer vision to real datasets through academic projects, internships, industry roles, or open-source work, with evidence of hands-on model development and evaluation.
- Top Technical and interpersonal skills: Proficiency in Python and familiarity with ML/CV libraries such as scikit-learn, PyTorch or TensorFlow, and OpenCV; understanding of core ML concepts and basic deep learning; and a collaborative, clear-communicating working style.
PREFERRED QUALIFICATIONS
What will give you a competitive edge (preferred qualifications):
- Scientific data and project experience: Exposure to scientific datasets (e.g., high-content imaging, histopathology, microscopy, behavioral video, assay data) and completed projects, theses, or publications showing applied ML/CV skills with scientific or healthcare relevance.
- Technical craft and tooling: Familiarity with training deep learning models on GPUs, use of Git and reproducible workflows, and exposure to data platforms or cloud environments such as Databricks, Azure, or AWS.
- Growth orientation and initiative: Demonstrated ability to learn quickly, iterate on models and analyses, and contribute to reusable code, tools, or documentation that improve team efficiency and quality.
ADDITIONAL INFORMATION
- Travel: Up to 10%
- Location: Global Elanco Headquarters - Indianapolis, IN – Hybrid Work Environment
Elanco Benefits and Perks:
We offer a comprehensive benefits package focusing on financial, physical, and mental well-being while encouraging our employees to pursue our purpose! Some highlights include:
- Multiple relocation packages
- Two weeklong shutdowns (mid-summer and year-end) in the US (in addition to PTO)
- 8-week parental leave
- 9 Employee Resource Groups
- Annual bonus offering
- Flexible work arrangements
- Up to 6% 401K matching
Elanco is an EEO/Affirmative Action Employer and does not discriminate on the basis of age, race, color, religion, gender, sexual orientation, gender identity, gender expression, national origin, protected veteran status, disability or any other legally protected status
Elanco may use automated tools, including AI, to support parts of our recruitment process, such as reviewing applications against job-related criteria and/or transferrable skills. These tools help ensure a consistent, structured evaluation, but they do not make hiring decisions. All decisions involve a human reviewer. For more information on how we handle personal data, please see our Elanco Workforce Privacy Notice.
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Get Access To All JobsTips for Finding OPT Sponsorship as a Computer Vision Engineer
Target STEM-designated programs first
Computer Vision Engineering falls squarely under STEM OPT eligibility. Confirm your degree's CIP code qualifies before applying, and prioritize employers with established E-Verify enrollment, which is required for your 24-month STEM extension.
Lead with your technical stack in applications
Employers scanning OPT candidates want to see PyTorch, OpenCV, CUDA, and specific architecture experience like YOLO or Transformers upfront. Put these in your resume summary, not buried under bullet points, to pass automated screening quickly.
Pursue research-to-industry pipelines
Many Computer Vision roles at companies like Waymo, Apple, and NVIDIA grow directly from academic research relationships. University lab publications, conference papers at CVPR or ICCV, and internship conversions are strong sponsorship entry points worth prioritizing.
File your STEM OPT extension early
Submit your STEM OPT extension application at least 90 days before your initial OPT expires. Your DSO must update your SEVIS record, and USCIS processing can take weeks, so do not wait until the final month.
Address OPT timing proactively with hiring managers
Mention your OPT end date and STEM extension eligibility in early conversations. Employers unfamiliar with OPT often fear short authorization windows, so explaining the three-year total timeline removes hesitation before it becomes a rejection reason.
Build a portfolio demonstrating real-world deployment
Hiring managers for Computer Vision roles want evidence you can take models from research to production. Publicly available GitHub projects showing inference optimization, edge deployment, or dataset annotation pipelines significantly strengthen sponsorship conversations with engineering managers.
Computer Vision Engineer OPT: Frequently Asked Questions
Can I work as a Computer Vision Engineer on OPT without H-1B sponsorship right away?
Yes. OPT authorizes full-time employment in your field for 12 months initially, with a 24-month STEM extension available if your degree qualifies and your employer is E-Verify enrolled. Most Computer Vision roles at tech and defense companies meet those conditions, giving you up to three years of authorized work before H-1B visa sponsorship becomes necessary.
Do Computer Vision Engineer roles typically qualify for the STEM OPT extension?
Computer Vision Engineering positions almost always qualify because the underlying degrees, typically computer science, electrical engineering, or applied mathematics, carry STEM-designated CIP codes. The role itself must also be directly related to that field of study, which is straightforward to document for computer vision work. Your DSO will confirm your specific degree qualifies before filing.
Which types of employers are most likely to sponsor OPT Computer Vision Engineers for H-1B?
Autonomous vehicle companies, robotics firms, semiconductor manufacturers, and defense contractors consistently sponsor Computer Vision Engineers at high rates because the skill set is specialized and hard to source domestically. Large tech companies building camera-based products also sponsor regularly. Migrate Mate filters job listings by visa sponsorship history, making it straightforward to identify which employers actively hire OPT candidates in this role.
Does contract or consulting work count toward OPT for Computer Vision Engineering positions?
Yes, contract work can count toward OPT as long as it is directly related to your degree field and meets the minimum 20-hours-per-week requirement during standard OPT. However, for the STEM OPT extension, your employer must be a formal E-Verify participant and provide a training plan on Form I-983. Short-term project contracts through staffing agencies often do not satisfy these conditions, so verify compliance carefully.
How should I handle the gap between OPT expiration and H-1B approval as a Computer Vision Engineer?
If your employer files an H-1B petition before your OPT expires and USCIS issues a receipt notice, cap-gap protections automatically extend your OPT authorization through September 30 of that year. Computer Vision Engineers with approved H-1B petitions starting October 1 are fully covered by this bridge. Plan your STEM OPT end date and H-1B filing timeline together with your employer's immigration attorney well in advance.