Associate ML & Gen AI Enigneer

Location : Pune, Onsite(WFO) Department : Engineering / Data & AI Experience : 2-3 years in ML & Gen AI Job Summary We are seeking an Associate Machine Learning Engineer of exposure and experience in developing AI solutions, including Generative AI, classical ML models, and data engineering pipelines. You will play a hands-on role in building and deploying scalable ML and GenAI applications. Key Responsibilities - Generative AI Development Design and implement applications using large language models (LLMs). Optimize prompts using techniques such as Chain of Thought, Few-Shot Learning, and RAG. Build scalable APIs and pipelines for GenAI -powered features. Machine Learning Engineering Build and deploy ML models (classification, regression, recommendation, etc.). Apply MLOps practices for model training, testing, deployment, and monitoring. Data Engineering Build and maintain data pipelines using Python and cloud-native tools. Ensure availability, scalability, and quality of data used in AI workflows. Work closely with backend and other engineering teams to integrate data systems. Model Deployment & Maintenance Deploy ML models via APIs, containers, or cloud services. Monitor production models and optimize their performance and scalability. Qualifications Required: 2 - 3 years of hands-on experience in Machine Learning (ML) and Generative AI. Mandatory: At least 1 year of recent experience working on Agentic AI workflows. Proficiency in Python and ML/AI frameworks and libraries such as Hugging Face, LangChain , and OpenAI . Strong experience in building APIs and deploying AI solutions in production environments. Experience in data pipeline development. Exposure to GenAI and ML/AI projects will be an added advantage. Preferred Candidates from reputed institutions are preferred (Tier 1 / UGC-approved, NAAC-accredited with A+ grade, and NBA-accredited for all UG programs). Exposure to classical ML or DL in production. Prior experience in early-stage/startup environments Candidates from reputed institutions are preferred (Tier 1 / UGC-approved, NAAC-accredited with A+ grade, and NBA-accredited for all UG programs). Understanding of cloud platforms (Azure preferred). Location : Pune, Onsite(WFO) Department : Engineering / Data & AI Experience : 2-3 years in ML & Gen AI Job Summary We are seeking an Associate Machine Learning Engineer of exposure and experience in developing AI solutions, including Generative AI, classical ML models, and data engineering pipelines. You will play a hands-on role in building and deploying scalable ML and GenAI applications. Key Responsibilities - Generative AI Development Design and implement applications using large language models (LLMs). Optimize prompts using techniques such as Chain of Thought, Few-Shot Learning, and RAG. Build scalable APIs and pipelines for GenAI -powered features. Machine Learning Engineering Build and deploy ML models (classification, regression, recommendation, etc.). Apply MLOps practices for model training, testing, deployment, and monitoring. Data Engineering Build and maintain data pipelines using Python and cloud-native tools. Ensure availability, scalability, and quality of data used in AI workflows. Work closely with backend and other engineering teams to integrate data systems. Model Deployment & Maintenance Deploy ML models via APIs, containers, or cloud services. Monitor production models and optimize their performance and scalability. Qualifications Required: 2 - 3 years of hands-on experience in Machine Learning (ML) and Generative AI. Mandatory: At least 1 year of recent experience working on Agentic AI workflows. Proficiency in Python and ML/AI frameworks and libraries such as Hugging Face, LangChain , and OpenAI . Strong experience in building APIs and deploying AI solutions in production environments. Experience in data pipeline development. Exposure to GenAI and ML/AI projects will be an added advantage. Preferred Candidates from reputed institutions are preferred (Tier 1 / UGC-approved, NAAC-accredited with A+ grade, and NBA-accredited for all UG programs). Exposure to classical ML or DL in production. Prior experience in early-stage/startup environments Candidates from reputed institutions are preferred (Tier 1 / UGC-approved, NAAC-accredited with A+ grade, and NBA-accredited for all UG programs). Understanding of cloud platforms (Azure preferred).