AI/ML Developer (CE58SF RM 3260)

Job Description

Position: AI/ML Developer (CE58SF RM 3260) Candidate Roles and Responsibilities Develop and implement machine learning models and algorithms. Work closely with project stakeholders to understand requirements and translate them into deliverables. Utilize statistical and machine learning techniques to analyze and interpret complex data sets. Stay updated with the latest advancements in AI/ML technologies and methodologies. Collaborate with cross-functional teams to support various AI/ML initiatives. Good to have Skills Knowledge and Experience in building knowledge graphs in production. Understanding of multi-agent systems and their applications in complex problem-solving scenarios. Technical Skills required: Solid Experience in Time Series Analysis, Anomaly Detection and traditional machine learning techniques such as Regression, Classification, Predictive modeling, Clustering, Deep Learning stack using python Experience with cloud infrastructure for AI/ ML on AWS(Sagemaker, Quicksight,Athena, Glue). Expertise in building enterprise grade, secure data ingestion pipelines for unstructured data(ETL/ELT) – including indexing, search, and advance retrieval patterns. Proficiency in Python, TypeScript, NodeJS, ReactJS (and equivalent) and frameworks. (e.g., pandas, NumPy, scikit-learn, SKLearn, OpenCV, SciPy), Glue crawler, ETL Experience with data visualization tools (e.g., Matplotlib, Seaborn, Quicksight). Knowledge of deep learning frameworks (e.g., TensorFlow, Keras, PyTorch). Experience with version control systems (e.g., Git, CodeCommit). Strong knowledge and experience in Generative AI/ LLM based development. Strong experience working with key LLM models APIs (e.g. AWS Bedrock, Azure Open AI/ OpenAI) and LLM Frameworks (e.g. LangChain, LlamaIndex). Knowledge of effective text chunking techniques for optimal processing and indexing of large documents or datasets. Proficiency in generating and working with text embeddings with understanding of embedding spaces and their applications in semantic search and information. retrieval. Experience with RAG concepts and fundamentals (VectorDBs, AWS OpenSearch, semantic search, etc.), Expertise in implementing RAG systems that combine knowledge bases with Generative AI models. Knowledge of training and fine-tuning Foundation Models (Athropic, Claud , Mistral, etc.), including multimodal inputs and outputs. ******************************************************************************************************************************************* Job Category: Embedded HW_SW Job Type: Full Time Job Location: AhmedabadIndorePune Experience: 5 - 8 Years Notice period: 0-15 days