AI Team Lead

Genzeon Global; Hyderabad; On-site; INR 4,500,000 - 7,500,000; Full time

Job summary

Genzeon Global is seeking an experienced Senior AI/ML Lead to design, develop, and deploy ML/DL models addressing healthcare and business use cases. You will build robust feature pipelines, conduct rigorous evaluations, and apply NLP and LLM techniques for industry-specific solutions.

Ideal candidates have 9+ years in AI/ML, strong Python and library expertise, plus cloud and MLOps experience. You will collaborate with product and engineering teams to translate complex problems into actionable

Qualifications

• 9+ years of hands-on experience in AI/ML model development and deployment.
• Strong understanding of machine learning, deep learning, neural networks, and optimization algorithms.
• Proficiency in Python and AI/ML libraries (PyTorch, TensorFlow, Scikit-Learn, Pandas, NumPy).
• Experience with NLP libraries (Hugging Face Transformers, spaCy, NLTK).
• Hands-on experience with LLM fine-tuning, prompt engineering, and transformer-based models.
• Experience with SQL and/or NoSQL databases and data manipulation at scale.
• Knowledge of cloud platforms (AWS/Azure), Docker, and ML deployment workflows.
• Strong analytical, problem-solving, and communication skills.

Responsibilities

• Design, develop, and deploy ML/Deep Learning models for classification, regression, clustering, forecasting, anomaly detection, and predictive analytics.
• Build and optimize feature engineering pipelines and data preprocessing workflows for structured and unstructured datasets.
• Conduct EDA to identify trends and insights from large-scale healthcare and business datasets.
• Develop and evaluate models using appropriate metrics, cross-validation, and experimentation frameworks.
• Implement NLP solutions for text classification, entity extraction, summarization, and information retrieval.
• Design and fine-tune LLMs for domain-specific applications and transfer learning.

Skills

Python

ML frameworks

NLP

LLMs

Prompt engineering

SQL/NoSQL

Cloud platforms

Docker

Data analysis

Communication

Tools

PyTorch

TensorFlow

Scikit-Learn

Pandas

NumPy

HuggingFace Transformers

spaCy

NLTK

Docker

AWS/Azure

Job description

• Design, develop, and deploy machine learning and deeplearning models for classification, regression, clustering,forecasting, anomaly detection, and predictive analytics use cases.
• Build and optimize feature engineering pipelines and datapreprocessing workflows for structured and unstructured datasets.
• Perform exploratory data analysis (EDA) to identifytrends, patterns, and actionable insights from large-scale healthcare andbusiness datasets.
• Develop and evaluate models using appropriatemetrics, cross-validation, and experimentation frameworks.
• Implement NLP solutions for text classification, entityextraction, summarization, and information retrieval .
• Design and fine-tune Large Language Models (LLMs) andtransformer-based architectures for domain-specific applications.
• Apply transfer learning and prompt engineering techniques to adapt foundation models to business and healthcare use cases.
• Build AI-driven document intelligence solutionsusing models such as LayoutLM, Donut, and Table Transformers forkey-value extraction and document understanding.
• Support MLOps and model deployment , includingDocker-based packaging, cloud deployment, monitoring, and performanceoptimization.
• Collaborate with product, engineering, andbusiness teams to translate business problems into AI/ML and GenAI solutions.
• Research and experiment with emerging AItechnologies, including RAG (Retrieval-Augmented Generation), LLM alignmenttechniques (RLHF, DPO, PPO, KTO), and model optimization methods .

Requirements

• 9+ years of hands-on experience in AI/ML modeldevelopment and deployment.
• Strong understanding of machinelearning, deep learning, neural network architectures, training methodologies,and optimization algorithms.
• Proficiency in Pythonand AI/ML libraries such as PyTorch,TensorFlow, Scikit-Learn, Pandas, and NumPy.
• Experience with NLPlibraries such as Hugging FaceTransformers, spaCy, and NLTK.
• Hands-on experience with LLMfine-tuning, prompt engineering, and transformer-based models.
• Experience with SQLand/or NoSQL databases and data manipulation at scale.
• Knowledge of cloudplatforms (AWS/Azure), Docker, and ML deployment workflows.
• Strong analytical, problem-solving, andcommunication skills, with the ability to explain complex AI concepts totechnical and non-technical stakeholders.

Preferred Skills

• Experience with RAG architectures, vector databases, embeddings, andsemantic search .
• Familiarity with LLM alignment techniques such as RLHF, DPO, PPO, and KTO .
• Experience with computer vision or document AI models forOCR and document understanding.
• Knowledge of Airflow or other workflow orchestration tools .
• Experience working with HIPAA, PHI, PII, or GDPR-compliant systems .
• Familiarity with Linux, Git, Jupyter Notebooks, and Agile developmentpractices .
• Experience with distributed computing and scalable AI infrastructure is a strong advantage.