Job Description

JD for Generative AI.
Role Description: We are looking for a passionate and skilled Generative AI & Machine Learning Engineer with 4 to 7 years of industry experience. You will be responsible for designing, developing, ML models with a strong focus on generative AI technologies, including LLMs, transformers, and foundation models. This role involves working on real-world applications such as chatbots, document summarization, content generation, and more.Key Responsibilitieso Build and fine-tune Generative AI models (LLMs, diffusion models, etc.) for various applications.o Work with agent and multi-agent frameworks to build task-specific or collaborative AI systems.o Develop and deploy ML pipelines for training, inference, and evaluation.o Collaborate with cross-functional teams (Product, Data Engineering, DevOps) to integrate ML models into products.o Conduct data preprocessing, exploratory analysis, and feature engineering.o Stay updated with state-of-the-art research in ML/GenAI and apply it to practical problems.o Optimize models for performance, scalability, and efficiency.o Work with APIs like OpenAI, AZURE OpenAI, and others for rapid prototyping and deployment.o Contribute to internal tools and frameworks to support ML experimentation and monitoring.Required Skills & Qualificationso Bachelor's or Master's degree in Computer Science, Data Science, AI/ML, or related field.o 3 to 5 years of hands-on experience in Machine Learning and/or NLP projects.o Proficiency in Python and popular ML libraries (e.g., PyTorch, TensorFlow, Hugging Face Transformers).o Practical experience with agent and/or multi-agent frameworks (e.g., LangGraph, CrewAI, AutoGen, AutoGPT, BabyAGI, etc.) is highly desirable.o Experience working with LLMs (GPT, Claude, etc.).o Familiarity with prompt engineering, RAG (Retrieval-Augmented Generation), and fine-tuning techniques.o Strong understanding of data structures, algorithms, and ML concepts.o Experience in deploying models using tools like Docker, FastAPI, Flask, or MLflow.o Knowledge of cloud platforms (AWS, GCP, or Azure) is a plus.Nice-to-Haveo Experience with vector databases (e.g., PG Vector, Pinecone, Weaviate).o Knowledge of MLOps tools (e.g., MLflow, Kubeflow, Airflow).o Publications or contributions to open-source projects in ML/GenAI.o Familiarity with ethical AI principles and responsible AI practices.
Competencies: Generative AI