Developer - AI/ML

Mode of Interview – F2F

Loc – Sec-62, Noida

Shift Timings - 2:30 PM - 11:30 PM IST

AI/ML Developer (Mid-Level) — NLP & Generative AI

About the Role

We are looking for an AI/ML Developer with a strong focus on Natural Language Processing (NLP) and Generative AI to join our team and having experience of 5+ years.

You will design, build, and deploy ML/LLM-based solutions that power intelligent features across our products, including chatbots, semantic search, document understanding, and generative content applications.

Experience Required

• 1–3 years of hands-on experience in Machine Learning / Deep Learning development
• At least 1–2 years of specific experience working with NLP and/or LLM-based systems

Key Responsibilities

• Design, develop, and fine-tune NLP models for tasks such as text classification, NER, summarization, and question-answering
• Build and optimize applications using Large Language Models (LLMs), including prompt engineering, fine-tuning, and RAG (Retrieval-Augmented Generation) pipelines
• Develop and maintain vector search/embedding-based retrieval systems
• Collaborate with product and engineering teams to integrate ML/LLM capabilities into production applications
• Evaluate and benchmark model performance (accuracy, latency, cost, hallucination rate)
• Deploy and monitor models in production environments
• Stay current with the latest research and tools in NLP and Generative AI, and evaluate their applicability to business use cases

Required Skills

Programming & Core Technical

• Strong proficiency in Python
• Experience with SQL for data querying
• Solid understanding of data structures, algorithms, and object-oriented programming

NLP & LLM Specific

• Hands-on experience with Hugging Face Transformers
• Experience with LLMs (OpenAI, Anthropic Claude, Llama, Mistral, etc.) via APIs or self-hosted deployment
• Prompt engineering and prompt optimization techniques
• Experience fine-tuning LLMs (LoRA, QLoRA, PEFT) or training custom NLP models
• RAG (Retrieval-Augmented Generation) architecture and implementation
• Vector databases (Pinecone, FAISS, or similar)
• Text embeddings and semantic search
• Tokenization, text preprocessing, and language model evaluation metrics

ML/DL Frameworks & Libraries

• PyTorch and/or TensorFlow
• Scikit-learn
• Pandas, NumPy
• LangChain, LlamaIndex, or similar LLM orchestration frameworks

ML Fundamentals

• Supervised/unsupervised learning, classification, clustering
• Model evaluation and validation techniques
• Feature engineering
• Understanding of overfitting, bias-variance tradeoff, and regularization

MLOps & Deployment

• Experience deploying models via REST APIs (FastAPI/Flask)
• Containerization with Docker
• Cloud platforms — AWS, GCP, or Azure
• Model versioning and experiment tracking (MLflow, Weights & Biases, DVC)

Data Handling

• Data cleaning, preprocessing, and pipeline development
• Experience working with large-scale unstructured text datasets
• Familiarity with distributed data processing (Spark or Dask) is a plus

Tools & Version Control

• Git/GitHub or GitLab
• Jupyter Notebooks
• Familiarity with Agile/Scrum development practices

If you are interested, please reply with your updated CV at [email protected]  along with the following details:

• Current CTC:
• Expected CTC:
• Notice Period:
• Total Experience:
• Relevant Experience:
• Current Location:
• Preferred Location: