Gurugram, Haryana, India
Information Technology
Full-Time
Eaton
Overview
What You’ll Do
- Implement and maintain the infrastructure needed for end-to-end machine learning workflows including data collection, model training, and deployment in production environments.
- Manage the lifecycle of large language models including training, evaluation, deployment, and monitoring of these models.
- Evaluate the performance of various machine learning models using appropriate metrics and statistical tests. Make recommendations on which models to use based on their performance.
- Fine-tune and enhance existing Retrieval Augmented Generation (RAG) and LLM models to improve their performance and adaptability.
- Design and optimize prompts to effectively guide the behavior of language models. Understand and manage the flow of prompts in a conversation or task(Prompt Engineering)
- Provide guidelines and strategies for improving the accuracy of machine learning models.
- Advise on how to optimize token usage to save costs and improve performance including strategies for efficient data preprocessing, model architecture design, and deployment.
- Leverage Azure AI technologies for developing, deploying, and managing AI solutions with Azure Machine Learning and Cognitive Services.
- Have knowledge and experience in deploying models and applications in cloud environments, particularly Azure.
- Bachelor’s degree in computer science, Data Science, or a related field. Advanced degree preferred.
- Overall 10+ Years of experience with 5 to 7 years of proven experience as an AI Engineer or similar role.
- Strong knowledge of machine learning algorithms and principles and Prompt engineering.
- Proficiency with Azure AI technologies including Azure Open AI
- Experience with MLOps, LLM Ops, model evaluation techniques, and Retrieval Augmented Generation.
- Strong programming skills, preferably in Python , experience with C# and .NET is a plus.
- Familiarity with models like LAMA , Mistral etc.
- Excellent problem-solving abilities and attention to detail.
- Strong communication skills and the ability to explain complex concepts to non-technical stakeholders.
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