Machine Learning Engineer

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.

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