AI/ML Engineer \xe2\x80\x93 Language Model Developer This role is for an experienced Artificial Intelligence Engineer on the Marketing Data Science team at HP. This individual will be responsible for helping the team to shape its AI strategy, specifically through the creation of AI models, such as Large Language models (LLMs) and Natural Language Processing (NLP), for Marketing. Marketers are tasked with combing through tons of research and data to find appropriate insights; there is oftentimes too much information and too little time. This individual will provide Marketers with curated AI tools that help them to have the right information at the right time to make the best decisions. This is a fantastic opportunity to be part of cutting-edge AI work that enables Marketing to drive innovation and business growth. Locations: Bucharest, Romania, On-site or Hybrid Education and Experience:
MS in Computer Science with an AI emphasis, or related field
2+ years of experience in applying AI to corporate technology solutions
Experience with cloud environments (Amazon Web Services, Google Cloud, Azure, Databricks)
Responsibilities:
Design the architecture and environment to enable AI models to run
Assess which environments are most appropriate, whether current compute is sufficient, whether we should choose an existing model or pretrain our own
Lead AI model construction to both evolve existing capabilities and create new ones
Apply AI to Marketing use cases to improve customer intelligence and data analytics
Teach Data Scientists how to use the created LLMs to analyze structured and unstructured data
Build AI applications and interfaces at scale for the bigger Marketing organization to use
Advise the team on best practices for AI models (i.e. parameters, data structure, etc.)
Evaluate LLM performance using different applications and file formats to identify the best solution
Debug and identify causality for issues in the AI results
Research new AI models and trends to understand how we can maximize the usage of our existing models and/or whether we should adopt new models
Knowledge and Skills:
Strong knowledge of ML and Deep Learning in the context of LLMs, NLPs and chatbots
Experience working with AI models using real-life (\xe2\x80\x9cindustry\xe2\x80\x9d) data