Job
Description
Role & responsibilities Architect and implement AI/ML solutions tailored to client-specific business problems using Gen AI (e.g., LLMs like GPT, Gemini, Mistral) and traditional ML models (e.g., scikit-learn, XGBoost). Collaborate with client stakeholders to understand requirements, define problem statements, and translate them into scalable AI/ML solutions. Present demos and proof-of-concepts (POCs) to clients, showcasing the value of AI/ML in real-world scenarios Mentor and guide a cross-functional team of data scientists, ML engineers, and developers Drive best practices in model development, deployment, and monitoring Stay abreast of the latest advancements in Gen AI and ML, and evaluate their applicability to client use cases Contribute to internal knowledge bases and reusable solution accelerators Preferred candidate profile Strong programming skills in Python and experience with ML libraries (e.g., TensorFlow, PyTorch, scikit-learn). Hands-on experience with Gen AI platforms and LLMs (e.g., OpenAI, Gemini, LLaMA, Mistral). Proven track record of deploying ML models in production environments (cloud/on-prem). Experience with API development, data pipelines, and dashboarding tools like Streamlit. Familiarity with DevOps and MLOps practices for model lifecycle management. Excellent communication and stakeholder management skills. Tools: LLM, SLM, Vector DB, Graph DB, Airflow, MLFlow, MLOps tools, NLP, KG, ML models (Regression, Clustering, Classification etc), LangChain, LangGraph, AutoGen
