Senior Data Scientist - Computer Vision

About the role

AB InBev is the leading global brewer and one of the world's top 5 consumer product companies. With over 500 beer brands, we're number one or two in many of the world's top beer markets, including North America, Latin America, Europe, Asia, and Africa. About AB InBev Growth Group Created in 2022, the Growth Group unifies our business-to-business (B2B), direct-to-consumer (DTC), Sales & Distribution, and Marketing teams. By bringing together global tech and commercial functions, the Growth Group allows us to fully leverage data and drive digital transformation and organic growth for AB InBev around the world. In addition to supporting well known global beer brands like Corona, Budweiser and Michelob Ultra, the Growth Group is home to a robust suite of digital products including our B2B digital commerce platform BEES, on-demand delivery services Ze Delivery and TaDa Delivery, and table top beer keg PerfectDraft. We are an exceptional team, focused on understanding and supporting consumer and customer needs, harnessing new technology, and scaling growth opportunities. The Senior Data Scientist will be responsible for developing and leading solutions at the intersection of Computer Vision, Computer Graphics, and Multimodal Models . This role involves tackling strategic challenges, combining traditional computer vision techniques with cutting-edge scene reconstruction and generative AI, focusing on detection, classification, visual similarity, synthetic data generation, and multimodal interpretation. You will act as a technical reference within the team, guiding architectural decisions and defining the best approaches for complex visual problems. You will work in a highly collaborative, global environment, transforming visual data into robust and scalable models, ensuring automation, efficiency, and high performance across implemented pipelines. We are looking for someone with an analytical mindset, curiosity, a strong technical foundation in the mentioned areas, excellent communication skills, a collaborative spirit, and a passion for innovation and continuous learning.

Responsibilities

• Define and lead the technical approach for object detection solutions (e.g., YOLO, RT-DETR, and similar architectures), applying them to real-world problems with an emphasis on performance, accuracy, and scalability.
• Define and develop image classification strategies, with experience in architectures such as EfficientNet, MobileNet, and ResNet, focusing on production readiness.
• Lead the development of Siamese networks for verification and visual similarity tasks, applying fine-tuning and optimization strategies for image comparison and visual integrity validation.
• Define and apply multimodal generative and instruction-following models such as Qwen-VL, PaliGemma, and BLIP, using fine-tuning techniques like LoRA and QLoRA, focusing on image-text alignment.
• Knowledge of scene reconstruction techniques such as NeRF or Gaussian Splatting, and hands-on experience with frameworks like Nerfstudio or similar.
• Work with large volumes of visual data, coordinating curation, annotation, and qualitative evaluation strategies to ensure diversity and quality in image datasets.
• Generate and use synthetic and 3D data as complementary sources for training and evaluating models, supporting their creation and curation to enhance model generalization and robustness.
• Automate, version, and monitor training, inference, and deployment pipelines using Python, PySpark, MLflow, GitHub Actions, Docker, and CI/CD, running on cloud infrastructure (especially Azure and Databricks).
• Mentor junior and mid-level data scientists, supporting their technical growth and ensuring quality across the team's deliverables.
• Communicate technical results and trade-offs to senior stakeholders, ensuring strategic alignment of developed solutions.
• Collaborate with data engineers, data scientists, PMs, and business stakeholders, ensuring technical alignment and strategic impact of developed solutions.
• Work in an agile, global environment, participating in Scrum/Kanban ceremonies, technical reviews, and continuous delivery and learning cycles.

Requirements

• Bachelor's degree in Computer Science, Engineering, Mathematics, or related fields. A master's or PhD is strongly preferred.
• General and foundational knowledge in data science and statistics, including data analysis, modeling, and validation techniques.
• Strong background in Deep Learning, including mastery of Transformer architectures and advanced algorithms applied to real-world problems.
• Proven experience building and deploying models for object detection, image classification, visual information extraction, and multimodal interpretation.
• Proficiency in TensorFlow or PyTorch, with experience in model development and deployment.
• Experience with cloud computing, particularly Azure, Databricks, and Spark, for large-scale data processing.
• Expertise in Python and PySpark, plus

Benefits

Your Match

How well this role fits your profile.

Company Intel

What employees say

Worked at abinbev? Share your experience