Senior Data Scientist - Computer Vision

About the Team

The computer vision and data science team at this global retail technology company focuses on advancing innovation while embedding safety and security within its operations. Their work includes fraud detection, threat management, and digital risk assessment, supporting cloud transformation to maintain security and trust. Through advanced analytics and data-driven insights, they enhance business decision-making and operational resilience. Collaboration and continuous improvement are key values, driving accuracy, security, and sustainable growth.

Role Responsibilities

• Develop, train, and implement computer vision models for object detection, personalized image-based services including product discovery, visual recommendations, and generative image content.
• Create and scale foundational model pipelines that combine multiple data modalities such as text, images, and customer embeddings to deliver personalized visual experiences.
• Provide mentorship to teammates on best practices and lead innovation in image generative modeling, including but not limited to diffusion models, convolutional neural networks, and text-to-image synthesis within retail contexts.
• Architect model workflows integrating with MLOps pipelines to ensure optimized performance, reduced latency, and ensure deployment and monitoring of models in production environments.
• Collaborate closely with cross-functional teams to translate business needs into effective data-driven solutions.
• Establish team-wide standards and reusable analytic frameworks.
• Work with engineering counterparts to guarantee models are production-ready concerning scalability, monitoring, and systems integration.
• Define modeling standards, review methodologies, and provide advanced technique guidance to junior members.
• Effectively communicate complex modeling outcomes and insights to senior leadership and stakeholders as actionable narratives.
• Identify new growth opportunities proactively and influence prioritization of the development roadmap.
• Act as a strategic advisor to cross-functional leadership on key initiatives to align efforts for high impact.
• Lead adoption of best practices in data science methodologies, experimentation approaches, and decision-making processes across the organization.

Required Skills and Experience

• Master’s or preferably PhD degree in Computer Science, Machine Learning, Computer Vision, Applied Mathematics, or a related field with over 7 years of professional or research experience.
• Proven expertise in deep learning for computer vision tasks, including convolutional neural networks, vision transformers, and diffusion generative models.
• Hands-on experience deploying production systems for image generation, manipulation, or understanding, such as visual search and personalized image recommendations.
• Strong proficiency with PyTorch, TensorFlow, OpenCV, torchvision, Hugging Face libraries, and GPU-enabled deepstream frameworks.
• Knowledge of multimodal AI models combining vision and language data like CLIP, BLIP, and Flamingo to enrich personalization and customer insights.
• Advanced skills in SQL and Python (including pandas, scikit-learn, and statsmodels), with experience analyzing large-scale datasets.
• Demonstrated success in scaling machine learning models within production environments.
• Sound understanding of experimentation design, causal inference, and statistical modeling techniques.
• Experience with cloud data ecosystems such as BigQuery and Spark, alongside mature data workflow pipelines.
• Familiarity with model tuning and optimization strategies like PEFT, LoRA, adapters, model distillation, and domain adaptation for efficient large language model customization.
• Competence in building retrieval and search systems employing embeddings, semantic/hybrid search, and vector databases like FAISS, Milvus, or Weaviate.
• Strong foundation in computer vision methodologies including image classification, object detection, semantic and instance segmentation using architectures such as ResNet, EfficientNet, ViT, and Swin transformers.
• Beneficial to have experience with generative AI methods including reinforcement learning with human feedback, retrieval-augmented generation, multi-agent system design, and scalable large language model contexts.
• Preferable experience with multimodal and generative models such as DINO, VQA, image captioning, Stable Diffusion, GANs, and video analysis models like VideoMAE.

About the Employer

This global technology arm of a leading retailer empowers innovation that impacts hundreds of millions worldwide. The company boasts a culture combining technology with people focus. Employees of diverse levels gain access to advanced skill development and participate in shaping the future of retail through technology. The role is based in the Bangalore office, with flexibility to support personal life balance.

Benefits and Culture

In addition to a competitive compensation package, the company offers performance incentives, comprehensive maternity and parental leave, paid time off, and robust health benefits. The organization is committed to building an inclusive workplace where diversity is celebrated and every individual is respected, fostering a sense of belonging. They embrace equal opportunities and value unique perspectives that enhance innovation and business success.