Specialist Full Stack AI Engineer

Job Summary

In Eaton, making our work exciting, engaging, meaningful; ensuring safety, health, wellness; and being a model of inclusion & diversity are already embedded in who we are - it's in our values, part of our vision, and our clearly defined aspirational goals.

This exciting role is part of our IT team in a large multi-national company. This role demands a candidate with experience in AI application development, including front-end and back-end components, user interfaces, and system integrations using .Net, JavaScript, Angular or React, SQL, and APIs.
The candidate should be proficient in deploying AI models using Azure, Kubernetes, and GitHub, and have a deep understanding of Azure AI services, NLP, computer vision, and GPT models.The role requires strong analytical skills, the ability to translate business requirements into AI solutions, and excellent communication skills to explain complex AI concepts to non-technical stakeholders. Collaboration with business leaders and architects is also essential.

Must have proven experience in building front-end and back-end components for AI applications, building/consuming APIs ,building customer centric user interfaces and designing integrations with other systems using .Net, JavaScript, Angular or React, SQL
Must have proven experience in solution deployment by packaging trained AI models as services using Azure deployment services, Kubernetes, and GitHub for version control.
Should have in depth understanding of Azure AI services such as Azure Machine Learning and Cognitive Services along with other AI technologies , natural language processing (NLP), computer vision and GPT models
Should have strong expertise in articulating and documenting solution architecture for AI projects by collaborating with solution architect and enterprise architects.
Must have abilities to collaborate with business leaders to understand their pain points and identify key areas where AI solutions can drive significant business benefit.
Must have strong analytical and problem-solving skills, with the ability to translate business requirements into effective AI solutions.
Must have excellent communication skills, with the ability to convey complex AI technical concepts to non-technical stakeholders.

Job Responsibilities

investigate and fix bugs; create automated test scripts.
- Maintain, operate, and monitor solutions
- Lead the development of prototype designs for a product using a wide range of techniques
- Demonstrate and document solutions by using flowcharts, diagrams, code comments, code snippets, and performance instruments. Guide others on the team in documenting their code.
- Recommend software tools to management and architecture teams
-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.
-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

Qualifications:

Bachelors in engineering/ B.E/B. Tech and/or required equivalent MCA.
Overall 12+ years' experience with proven track record of 5+ years in Solutioning and deploying end to end AI

Skills:

Net, JavaScript, Angular or React, SQL Server, Azure deployment services, Kubernetes, GitHub , Azure Cognitive Services , GPT models, added advantage with GitHub Copilot