Job Title : Senior Full-Stack AI / ML Engineer – Vision Analytics, LLMs & Hybrid Deployment
Location : Pune from KBL Baner Pune Office
Department : Corporate Information Centre (CIC)
Role Overview
As a Senior Full-Stack AI / ML Engineer at KBL, you will play a key role in developing and deploying intelligent systems that enhance operational efficiency, quality assurance, and customer experience. You will work on a range of use cases from vision-based quality inspection and predictive maintenance to LLM-driven document understanding and automation .
This role requires strong technical depth, independent ownership, and the ability to collaborate with cross-functional teams across engineering, IT, and business domains.
Key Responsibilities
- Lead the design, development, and deployment of AI / ML models across vision, language, and prediction use cases
- Develop and implement solutions using LLMs (e.g., LLaMA, Azure OpenAI) and Computer Vision frameworks (OpenCV, PyTorch, YOLO, etc.)
- Architect hybrid deployment models using Azure cloud and on-premises infrastructure , ensuring high availability and scalability
- Collaborate with internal stakeholders using design thinking to convert business needs into AI solutions
- Develop end-to-end ML pipelines (ETL, training, evaluation, inference, monitoring)
- Optimize performance of models for real-time inference and resource efficiency (GPU / CPU)
- Ensure best practices in CI / CD, containerization (Docker / Kubernetes), and model lifecycle management
- Support internal teams with documentation, training, and handover of AI tools and platforms
Required Qualifications & Experience
B.Tech from a premier engineering institute ; M.Tech preferred5+ years of relevant experience in AI / ML engineering and production deploymentsProficiency in Python , PyTorch , and deep learning toolsStrong experience with LLMs (e.g., LLaMA, GPT) and vision analytics for object detection, classification, and OCRProven ability to deploy models on Azure and on-prem environments with GPU accelerationFamiliarity with predictive modelling techniques in manufacturing / engineering contextsExcellent communication and stakeholder engagement skillsDesirable Skills (Good to Have)
Experience with digital twin models , edge computing , or smart factory systemsKnowledge of Hugging Face , vLLM , or other open-source LLM frameworksExposure to MLOps tools , API development (FastAPI), and automated model retrainingAwareness of data security , model interpretability , and ethical AI practicesSoft Skills & Role Readiness
Candidate should be self-driven and able to work independently with minimal guidanceStrong verbal and written communication skills to engage with business and technical teamsAbility to translate requirements into technical solutions using design thinking principlesComfortable with working in a manufacturing / industrial environment if required onsiteSupplier Responsibilities
Conduct a technical screening and validation before sharing profiles.Provide reference checks and past project verification (especially for AI / ML deployment experience)Take ownership of resource onboarding , handover coordination , and periodic performance feedback collection and assistanceProvide a backfill plan in case of early attrition or performance misalignment