Overview
Job Description Summary
We are looking for a technically skilled and impact-driven AI Engineer to design and develop advanced AI models across use cases such as multi-agent systems, (Graph) RAG, computer vision, and tabular prediction tasks. You will contribute across the full lifecycle of model experimentation, optimization, and production-readiness, collaborating closely with Data Engineers who handle orchestration and pipeline infrastructure. Operating from our Global Capability Center in Pune, you will work as part of a global team and play a key role in model innovation, scalable architecture design, and integration into production systems, with clear impact on business performance.
Key Responsibilities Model Development & Optimization
· Independently design and train robust, reusable AI/ML models using frameworks like Kubeflow, PyTorch, TensorFlow, or HuggingFace.
· Apply advanced techniques in deep learning, NLP, computer vision, and classical ML, ensuring models are explainable and scalable.
· Optimize models for accuracy, speed, and resource efficiency, and collaborate with Data Engineers on deployment readiness. AI/ML System
Design
· Translate business use cases into scalable AI model architectures, including design of pre-processing strategies and feature engineering approaches.
· Ensure alignment between data characteristics, model architecture, and expected system behavior in production.
· Collaborate on integration patterns with Data Engineers to embed AI models in downstream workflows. Documentation & Standards
· Write clear documentation on model assumptions, architecture choices, evaluation criteria, and recommended usage.
· Contribute to the standardization of model development guidelines within the AI team to ensure reproducibility and traceability.
Stakeholder Collaboration & Delivery
· Support scoping and delivery of AI features and enhancements within broader data product initiatives.
· Partner with domain experts, business stakeholders, and functional analysts to iterate on model design and results interpretation.
· Adapt solutions based on feedback and performance monitoring, ensuring business value is realized
Innovation & Capability Building
· Stay up to date on emerging AI/ML methods, tools, and frameworks, and explore how these can improve our modelling practices.
· Share findings and contribute to team learning sessions, playbooks, or prototyping initiatives. Security & Compliance in AI
· Design models with appropriate data privacy, access control, and bias mitigation considerations.
· Ensure models meet compliance, governance, and interpretability standards relevant to the business context.
Mentoring & Community
· Mentor junior AI engineers on modelling approaches, model evaluation, and development best practices.
· Contribute to a knowledge-sharing culture across the AI, data science, and engineering teams.
Required Qualifications
· Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related IT field.
· 3–10 years of experience designing and implementing AI/ML models in production.
· Experience working with Google Cloud is mandatory.
· Experience working Transformers, Embedding Techniques, Image Recognition, Reinforcement learning.
· Familiarity with Dockers.
· Strong Python development skills, with deep familiarity with ML/DL libraries (e.g., Kubeflow, PyTorch, TensorFlow, scikit-learn).
· Demonstrated success with real-world AI use cases, including agents, vision, or forecasting.
· Understanding of model lifecycle, versioning, monitoring, and deployment-readiness (in coordination with MLOps/ML Engineers).
· Strong ability to collaborate in cross-functional teams and communicate modelling choices to technical and non-technical audiences.