Become a **Lead AI/Computer Vision Engineer** driving the creation of advanced AI solutions that analyze visual content and personalize product recommendations.
You will spearhead the integration of computer vision, semantic image understanding, and behavioral AI into scalable intelligent systems. Join us to shape innovative AI technologies that elevate client experiences and deliver impactful results.
**Responsibilities**
- Develop and enhance CNN and transformer-based vision models for image evaluation and scoring
- Design and implement custom transformer architectures to support product development
- Build robust pipelines to handle high volumes of image data and produce structured metadata
- Deploy transformer-based models for tailored product recommendations
- Lead experimentation processes including A/B testing to optimize recommendation quality and conversion rates
- Manage and document the complete ML model lifecycle from development to deployment
- Collaborate with cross-functional teams to lead technical initiatives from concept through execution
- Ensure adherence to best practices in data handling, model assessment, explainability, and monitoring
**Requirements**:
- Extensive software engineering experience with over 5 years focused on AI/ML roles
- In-depth expertise in computer vision methods including CNNs, vision transformers, facial recognition, object detection, image classification, and embeddings
- Strong background in recommendation systems, collaborative filtering, deep learning personalization, and transformer-based recommendation techniques
- Proficiency in Python and ML frameworks such as PyTorch and TensorFlow
- Experience deploying machine learning models at scale using Docker, AWS, GCP, or equivalent platforms
- Demonstrated leadership in managing cross-functional technical projects from inception to delivery
- Comprehensive understanding of ML lifecycle best practices including data management, model evaluation, explainability, and observability




- Master’s degree in Computer Science or a related discipline, preferably with a math or physics emphasis
- English communication skills at B2 level or above
**Nice to have**
- Practical experience with diffusion models
- Knowledge of graph neural networks (GNNs)
- Understanding of reinforcement learning concepts
**We offer**
- Career plan and real growth opportunities
- Unlimited access to LinkedIn learning solutions
- Constant training, mentoring, online corporate courses, eLearning and more
- English classes with a certified teacher
- Support for employee’s initiatives (Algorithms club, toastmasters, agile club and more)
- Enjoyable working environment (Gaming room, napping area, amenities, events, sport teams and more)
- Adaptable work schedule and dress code
- Collaborate in a multicultural environment and share best practices from around the globe
- Hired directly by EPAM & 100% under payroll
- Law benefits (IMSS, INFONAVIT, 25% vacation bonus)
- Major medical expenses insurance: Life, Major medical expenses with dental & visual coverage (for the employee and direct family members)
- 13 % employee savings fund, capped to the law limit
- Grocery coupons
- 30 days December bonus
- Employee Stock Purchase Plan
- 12 vacations days
- Official Mexican holidays, plus 5 extra holidays (Maundry Thursday and Friday, November 2nd, December 24th & 31st)
- Monthly non-taxable amount for the electricity and internet bills
EPAM is a leading global provider of digital platform engineering and development services. We are committed to having a positive impact on our customers, our employees, and our communities. We embrace a dynamic and inclusive culture. Here you will collaborate with multi-national teams, contribute to a myriad of innovative projects that deliver the most creative and cutting-edge solutions, and have an opportunity to continuously learn and grow. No matter where you are located, you will join a dedicated, creative, and diverse community that will help you discover your fullest potential.

📌 Lead Ai/computer Vision Engineer (México)
🏢 Epam Systems
📍 México