Data Scientist - Computer Vision

Overview

Design, build and deploy AI and Machine Learning solutions, with a focus on Computer Vision, Deep Learning, Generative AI and NLP, and work with engineering teams to put models into production.

What you'll do

• Translate consumer, product and business challenges into well-defined Data Science and AI problems.
• Analyse complex and high-dimensional datasets and formulate hypotheses and proof-of-concepts.
• Design, develop and evaluate Machine Learning and Deep Learning models.
• Build solutions using Computer Vision, NLP, Generative AI and LLM-based techniques, depending on the use case.
• Evaluate state-of-the-art AI/ML approaches and apply appropriate techniques to complex business problems.
• Develop AI-based Computer Vision applications for image-related use cases.
• Apply modern deep-learning architectures and frameworks, including approaches such as YOLO and U-Net, where appropriate.
• Work with image-processing and feature-extraction techniques and develop robust model-training and evaluation pipelines.
• Develop solutions using LLMs, Transformers, RAG architectures and agentic frameworks.
• Apply NLP approaches for extracting and representing information from unstructured data.
• Evaluate GenAI solutions for quality, reliability and suitability for the intended application.
• Perform exploratory data analysis, data cleansing, preprocessing, feature engineering and statistical analysis.
• Ensure data quality, accuracy and reliability through validation and quality-control approaches.
• Establish reproducible methodologies and document experiments, assumptions, results and analytical findings.
• Participate in the end-to-end deployment and testing of Data Science solutions.
• Work closely with engineering teams to integrate AI models into production applications and enterprise workflows.
• Monitor and continuously improve deployed model performance.
• Contribute to robust and scalable data pipelines supporting advanced analytics and ML solutions.
• Collaborate with Data Engineers, Software Engineers, product/business stakeholders and other cross-functional teams to operationalise Data Science solutions.
• Communicate complex analytical results and recommendations clearly to stakeholders.
• Contribute to knowledge sharing, technical documentation and Data Science methodologies.
• Mentor Data Scientists and contribute to building Data Science competency within the organisation.

What you'll need

• 7-10 years experience in AI and Data Science field.
• Master's in computers, electronics, electrical engineering or PhD in relevant streams.
• Strong hands-on experience in several of the following: Python and Data Science/ML ecosystem; Machine Learning and statistical modelling; Deep Learning; PyTorch / TensorFlow; Computer Vision and OpenCV; Image processing and AI-based vision applications; NLP and Transformer LLMs and Generative AI; Retrieval-Augmented Generation (RAG); Agentic AI frameworks; Classical ML approaches such as regression, Random Forest, SVM and k-NN; Statistical testing and experimental analysis; Data preparation, validation and quality assessment.

Details

• Location: Bangalore.
• Work mode: office-based role, working in-person at least 3 days per week.