Gen AI Lead
E-Solutions - Dallas, TX
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Role: Gen AI Lead Location: Dallas, TX (Hybrid) Mandatory Skills-Gen AI/Agentic AI /ML JOB DESCRIPTION: 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 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, NetCracker, CSG etc.) Preferred Qualifications: Certification in AI/ML, Deep Learning, or Generative AI is a plus.
Created: 2026-03-10