What are the responsibilities and job description for the Gen AI Led position at Yochana IT Solutions?
Job Details
Keywords: AI/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, ThoughtSpot, 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, SAS
Gen AI & Agents Prompt Engineering, RAG, Vector DB, Agentic Frameworks, MCP, Large Language Models (LLMs),LangChain, LangGraph, Explainable AI, Conversational AI, Chat bots and Tuning, LLM Evaluations and Cost monitoring, HuggingFace
Tools/Framework: Git, TensorFlow, PyTorch, PySpark, AWS, MLflow, Docker, Kubernetes, Databricks, SparkSQL, OpenCV, Azure, YOLO, Scikit-Learn, FastAPI, Flask, Django, Keras, Pandas, NumPy, Polars, SciPy, Matplotlib, Seaborn,Plotly, Streamlit
Cloud & MLOps: AWS Sagemaker, Azure ML, or Google Cloud Platform 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, Google Cloud Platform).
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
o Telecom BSS & OSS domain and understanding of fixed, mobile, IoT & convergence domains and related markets
o Business Systems (BSS)- Understanding of E2E BSS Solutions across Sales, Marketing, Finance, Product Management, Care areas for CSPs.
o Knowledge on data integration for telecom industry B/OSS COTS & Data Models ( Amdocs, NetCracker, CSG etc.)
Preferred Qualifications:
Certification in AI/ML, Deep Learning, or Generative AI is a plus.