Artificial Intelligence Engineer

Role: AI Engineer
Company: Webnyay Private Limited
Location: Pune
Employment Type: Full-time
Experience: 5+ years in ML Engineering, NLP and Generative AI
Education: B.E./B.Tech/M.Tech in AI/ML or equivalent

About the Role

Webnyay Private Limited is looking for an experienced AI Engineer to design, develop, deploy and optimize self-hosted AI/ML solutions, with a focus on text classification, Natural Language Processing (NLP) and Generative AI workflows.

The ideal candidate will have strong Python and deep learning expertise, hands-on experience with open-weight Large Language Models (LLMs), retrieval-augmented generation (RAG), and production-grade model deployment. The role involves building secure, scalable AI solutions for enterprise and regulatory use cases, including a flagship deployment at a public sector undertaking.

Key Responsibilities

AI/ML Model Development

• Design, develop and deploy machine learning models for enterprise text classification and NLP use cases.
• Build production-ready workflows for text classification, named entity recognition (NER), summarisation and Generative AI.
• Fine-tune open-weight LLMs using techniques such as LoRA and QLoRA.
• Develop and optimize retrieval-augmented generation (RAG) pipelines.
• Evaluate model performance using appropriate metrics, calibration techniques and validation frameworks.

Self-Hosted LLM and Model Deployment

• Deploy and operate open-weight AI models in self-hosted environments using inference servers such as vLLM, Hugging Face TGI or Ollama.
• Optimize model inference on GPU and CPU infrastructure.
• Expose ML models through REST APIs using FastAPI or similar frameworks.
• Package and deploy AI services using Docker.
• Optimize inference latency, throughput, resource utilization and reliability.

Data Protection and Responsible AI

• Implement appropriate handling of personally identifiable information (PII) in AI/ML pipelines.
• Apply data protection and security best practices throughout model development, training, inference and storage.
• Support model evaluation, validation, monitoring and production troubleshooting.
• Collaborate with engineering, product and QA teams to integrate AI workflows into enterprise applications.

MLOps and Production Engineering

• Build repeatable model training, evaluation and deployment pipelines.
• Track experiments, manage model versions and monitor model performance.
• Support model drift monitoring and continuous improvement of production AI systems.
• Work with vector databases and retrieval systems to improve the accuracy and relevance of AI-generated responses.

Required Skills and Qualifications

• B.E./B.Tech/M.Tech in AI/ML or an equivalent qualification.
• 5+ years of experience in ML Engineering, including hands-on delivery of production NLP, classification and Generative AI workflows.
• Strong programming skills in Python.
• Practical experience with PyTorch and Hugging Face Transformers.
• Hands-on experience fine-tuning open-weight LLMs using LoRA, QLoRA or similar techniques.
• Strong understanding of RAG architectures, embeddings, retrieval and context management.
• Experience deploying self-hosted models using vLLM, TGI, Ollama or similar inference servers.
• Experience with GPU/CPU inference optimization and model serving.
• Strong understanding of text classification, named entity recognition (NER), summarisation and model evaluation metrics.
• Experience building model APIs using FastAPI or similar frameworks.
• Proficiency in Docker and production deployment practices.
• Understanding of PII handling, data privacy and data protection in ML systems.

Good to Have

• Experience with NLP for Indian languages, particularly Hindi and regional languages.
• Exposure to speech-to-text systems and multilingual AI workflows.
• Experience working with BFSI, banking, NBFC or legal text.
• Familiarity with MLOps tools such as MLflow for experiment tracking, model registry and drift monitoring.
• Experience with vector databases such as pgvector, Qdrant or Milvus.
• Familiarity with the Digital Personal Data Protection (DPDP) Act, 2023, RBI guidance on AI, or model risk management.
• Published research, open-source contributions or strong Kaggle results in NLP or machine learning.

What We Offer

• Ownership of a Generative AI system deployed in production at a public sector undertaking.
• Opportunity to work with a small, experienced team where models move quickly from development to production.
• Exposure to the intersection of Generative AI, regulatory technology and consumer protection.
• An opportunity to solve real-world enterprise AI challenges involving secure, self-hosted models and NLP workflows.