Machine Learning Engineer - RAG/Generative AI

Responsibilities : - Design, develop, and deploy Machine Learning models and systems with a strong emphasis on Large Language Models (LLMs) and Generative AI techniques. - Utilize and optimize various prompt engineering techniques to elicit desired responses and behaviors from LLMs. - Implement and refine RAG pipelines to enhance the accuracy and contextuality of LLM outputs by integrating external knowledge sources. - Design and develop intelligent agents leveraging LLMs for various applications, such as automation, customer service, and content generation. - Lead GenAI client engagements, understanding their business needs, and translating them into technical requirements and solutions. - Align the engineering team towards a clear and achievable technical roadmap for GenAI projects, ensuring technical feasibility and strategic alignment. - Perform thorough business analysis and requirement gathering for Generative AI and traditional Machine Learning projects, working closely with business Subject Matter Experts (SMEs). - Design end-to-end solution workflows for GenAI/ML projects, including data ingestion, preprocessing, model development, deployment, and monitoring. - Leverage your understanding of cloud services (Azure, GCP, or AWS) to design and deploy scalable and robust ML solutions. - Utilize your strong programming skills in Python, Langchain, and SQL to develop and implement ML models and systems. - Effectively communicate complex technical concepts and project progress to both technical and non-technical stakeholders, including business SMEs and clients. - Integrate developed ML models and systems with existing software infrastructure and data pipelines. - Monitor the performance of deployed ML models and implement necessary optimizations for accuracy, latency, and scalability. - Continuously research and stay updated on the latest advancements in LLMs, Generative AI, and related machine learning Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field. - 10-15 years of professional experience in building Machine Learning models and systems, with a strong foundation in software engineering principles. - 3-4 years of focused experience working with Large Language Models (LLMs) such as GPT-3/4, PaLM, Llama, or similar. - 1 years of hands-on experience in applying Generative AI techniques, particularly prompt engineering, Retrieval-Augmented Generation (RAG), and the development of AI agents. - Must have strong programming skills in Python. - Hands-on experience with LLM frameworks and libraries, especially Langchain. - Proficiency in SQL for data manipulation and analysis. - Proven experience in leading client engagements, understanding business needs, and translating them into technical solutions. - Ability to align an engineering team towards a technical roadmap and provide technical guidance. - Demonstrated experience in performing business analysis, gathering requirements, and designing solution workflows for GenAI/ML projects. - Understanding of and experience with at least one major cloud service provider (Azure, GCP, or AWS) and their AI/ML offerings. - Excellent written and verbal communication skills, with the ability to effectively collaborate with business Subject Matter Experts (SMEs) and present technical information : - Experience with other relevant ML frameworks and libraries (TensorFlow, PyTorch, scikit-learn). - Experience with deploying and managing ML models in production environments. - Familiarity with MLOps practices and tools. - Experience with fine-tuning pre-trained LLMs on custom datasets. - Contributions to open-source ML projects or publications in the field. - Understanding of ethical considerations and responsible AI development practices. (ref:hirist.tech)

Location: in, IN

Posted Date: 5/1/2025