Senior AI Engineer

Your Role And Responsibilities

Senior AI Engineer, IBM Corporation, Armonk, NY and various unanticipated client sites throughout the US (Up to 20% telecommuting permitted):

• Manage broader responsibilities which includes leading AI system architecture, mentoring junior engineers, and driving strategic initiatives across multiple projects.
• Engages with stakeholders to align AI solutions with business objectives.
• Draft solution plays for Go-To-Market campaigns positioning AI Offerings.
• Lead engagements and conversations with clients to propose AI solutions offering the best price-performance value.
• Present to customer executives and at conferences AI solutions and architecture for use cases across different industries.
• Scale distributed computing workloads on clusters of GPU nodes in Cloud and On-Premises environments to train AI models.
• Utilize: Python; Machine Learning and Deep Learning Algorithms; Prompt Engineering of LLMs; Fine tuning of LLMs using LangChain; LangGraph; LlamaIndex and Pytorch frameworks; Spark.

Required: Master’s degree or equivalent in Computer Engineering, Artificial Intelligence (AI) and Data Science or related (employer will accept a Bachelor's degree plus five (5) years of progressive experience in lieu of a Master’s degree) and one (1) year of experience as a Senior AI Engineer or related. One (1) year of experience must include utilizing Python; Machine Learning and Deep Learning Algorithms; Prompt Engineering of LLMs; Fine tuning of LLMs using LangChain; LangGraph; LlamaIndex and Pytorch frameworks; Spark. $189,592 to $216700 per year. Full time. V169a.

Required Technical And Professional Expertise

Required: Master’s degree or equivalent in Computer Engineering, Artificial Intelligence (AI) and Data Science or related (employer will accept a Bachelor's degree plus five (5) years of progressive experience in lieu of a Master’s degree) and one (1) year of experience as a Senior AI Engineer or related. One (1) year of experience must include utilizing Python; Machine Learning and Deep Learning Algorithms; Prompt Engineering of LLMs; Fine tuning of LLMs using LangChain; LangGraph; LlamaIndex and Pytorch frameworks; Spark.