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 technologies.

Requirements:

- 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 clearly.

Nice-to-Have :

- 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.