Gen AI Lead

Gen AI Lead

Mandatory Skills - Gen AI/Agentic AI /ML

JOB DESCRIPTION:

/ML Development, Generative AI, LLMs, Python, Web Frameworks, MLOps, Data Engineering

Role Overview:
Sr AI/ML Lead with around 15+ years of hands-on experience in developing and implementing Machine Learning and Generative AI solutions. The role involves designing, developing, and deploying end-to-end AI/ML applications using Python, popular ML frameworks, and modern web technologies.

TECHNICAL

SKILLS:

Must Have Skills Machine learning development lifecycle - (Data preparation, Data visualization, Statistical Analysis, feature engineering, Predictive modeling, Model deployment, Model monitoring), CI/CD, MLOps, Generative AI, Causal Inference, Time series analysis, Forecasting, Anomaly detection, Hypothesis testing, A/B testing, Git Actions, Tableau, Power BI, Thought Spot, Web Scraping Data & Engineering – SQL, MySQL, Postgres, Spark, S3, Trino, Data Factory, ETL, Data pipelines, Databricks and distributed computing.

Programming

Languages:

SQL, Pyspark, Scala, R, Python, SASGen AI & Agents – Prompt Engineering, RAG, Vector DB, Agentic Frameworks, MCP, Large Language Models (LLMs),Lang Chain, Lang Graph, Explainable AI, Conversational AI, Chat bots and Tuning, LLM Evaluations and Cost monitoring, Hugging Face Tools /Framework:
Git, Tensor Flow, PyTorch, PySpark, AWS, MLflow, Docker, Kubernetes, Databricks, SparkSQL, OpenCV, Azure, YOLO, Scikit-Learn, FastAPI, Flask, Django, Keras, Pandas, Num Py, Polars, Sci Py, Matplotlib, Seaborn, Plotly, Streamlit Cloud & MLOps: AWS Sagemaker, Azure ML, or GCP AI Platform;
Git, Docker, CI/CD.

Role

Activities:

Design, develop, and deploy AI/ML and Generative AI models for enterprise and telecom use cases.

Build and optimize data pipelines for training, validation, and inference processes.

Develop web-based AI applications using frameworks like Flask, FastAPI, or Django.

Implement LLM-based solutions such as chatbots, summarization, and RAG-based systems.

Collaborate with data scientists, solution architects, and business teams to understand functional requirements and translate them into technical implementations.

Participate in proof-of-concept (PoC) development for AI/ML and automation use cases.

Conduct model evaluation, fine-tuning, and performance optimization.

Work with APIs, data sources, and cloud-based ML services (AWS, Azure, GCP).Follow best practices in MLOps, model versioning, and CI/CD integration.

Prepare technical documentation, training materials, and demo presentations.

Domain Skills Requirements:

At least 10+ years of experience in AI/ML development and Python-based solutions for Telco/Retail Domains Desired Domain Experienced Telecom BSS & OSS domain and understanding of fixed, mobile, IoT & convergence domains and related markets

Business Systems (BSS)- Understanding of E2E BSS Solutions across Sales, Marketing, Finance, Product Management, Care areas for CSPs.Knowledge on data integration for telecom industry B/OSS COTS & Data Models ( Amdocs, Net Cracker, CSG etc.)

Preferred Qualifications:

Certification in AI/ML, Deep Learning, or Generative AI is a plus.