Generative AI Engineer

Job Title: Generative AI Engineer

Location: Gurgaon (Hybrid)

Experience: 3+ Years

Notice Period: Immediate Joiners Preferred

Role Overview

We are looking for a highly skilled Generative AI Engineer to design and deploy advanced AI-driven search, recommendation, and LLM-powered systems. The ideal candidate will have strong hands-on experience with Transformer architectures, LLM fine-tuning, semantic search, and production-grade ML systems.

This role requires deep technical expertise in machine learning, natural language processing, and scalable deployment in enterprise environments.

Key Responsibilities

Search & Recommendation Development

- Lead end-to-end design, development, and deployment of search, personalization, and recommendation systems. - Build scalable solutions that significantly improve user experience and business KPIs. - Optimize ranking models and dense retrieval systems.

Transformer-Based Model Implementation

- Fine-tune and optimize models such as BERT, RoBERTa, and encoder architectures for: - Semantic Search - Relevance Ranking - Query Understanding - Embedding Generation - Implement dense vector search and retrieval systems.

Large Language Model (LLM) Innovation

- Research and prototype LLM-based solutions. - Work on model selection, prompt engineering, LoRA-based fine-tuning, and quantization. - Design and implement RAG (Retrieval-Augmented Generation) systems using vector databases. - Build advanced retrieval pipelines with frameworks such as Hugging Face, LangChain, and LlamaIndex.

⚙ ML Productionization (MLOps)

- Build, train, validate, and deploy ML models into scalable, low-latency production systems. - Ensure reliability, observability, and maintainability of ML services. - Collaborate with engineering teams to integrate models into real-world applications.

Data Strategy & Feature Engineering

- Work closely with Data Engineering to define datasets and feature pipelines. - Ensure data quality, consistency, and governance across ML workflows. - Develop innovative features for ranking and recommendation models.

Evaluation & Optimization

- Define and track KPIs such as NDCG, CTR, latency, perplexity, recall, and precision. - Continuously improve model accuracy, robustness, and performance. - Conduct A/B testing and experimentation.

Essential Technical Qualifications

- MS/PhD in Computer Science, Data Science, Engineering, or equivalent experience. - 3+ years of hands-on experience in ML/AI engineering. - Expert-level proficiency in Python. - Strong experience with ML/DL libraries (NumPy, Pandas, Scikit-learn). - Deep experience with PyTorch or TensorFlow. - Proven hands-on work with Transformer models (BERT, encoder-only models) for IR/NLU. - Practical experience with LLM fine-tuning and deployment. - Experience with frameworks such as Hugging Face, LangChain, LlamaIndex. - Strong understanding of classical ML algorithms and statistical modeling. - Direct experience building search ranking systems, recommendation engines, or vector-based search. - Experience with cloud platforms (AWS, GCP, or Azure). - Experience with MLOps tools such as MLFlow, Kubeflow, Docker, Kubernetes.

Preferred Qualifications

- Experience with LoRA, PEFT, or model quantization. - Hands-on work with vector databases (Pinecone, Weaviate, FAISS, Milvus). - Exposure to large-scale data systems and distributed training.

Why Join?

- Work on cutting-edge Generative AI systems. - High-impact role influencing search & recommendation architecture. - Collaborative and innovation-driven environment.