Artificial Intelligence Engineer

Role & responsibilities

Position Overview

The Engineer, Artificial Intelligence supports the development and deployment of advanced artificial intelligence solutions. This role focuses on implementing solutions that leverage Machine Learning, Natural Language Processing, and emerging technologies such as Generative AI and Large Language Models. The Engineer, Artificial Intelligence will work closely with data scientists, ML engineers, and product teams to translate business needs into scalable AI systems.

Essential Duties

Include, but are not limited to, the following:

• Support the execution of ML, NLP, LLM deliverables aligned with AI strategies.
• Contribute to the development of custom ML, Gen AI, NLP, LLM models for batch and stream processing-based AI ML pipelines including data ingestion, preprocessing modules, search and retrieval, Retrieval Augmented Generation (RAG), and NLP/LLM model development.
• Collaborate closely with data scientists, machine learning engineers, and software engineers to integrate AI models into production systems.
• Stay current with emerging AI/ML technologies and recommend innovative approaches.
• Apply best practices in data privacy, security, and biases in AI systems.

Minimum Qualifications:

• Bachelors degree in Computer Science, Artificial Intelligence, Data Science, or a related field; or High School Diploma/General Education Degree and 4+ years of relevant as outlined in the essential duties in lieu of Bachelor’s Degree.
• Professional experience in AI/ML model development.
• Demonstrated ability working with machine learning frameworks, programming languages like Python, and cloud platforms.
• Demonstrated ability to learn new technologies.
• Demonstrated understanding of ethical considerations in AI systems.
• Strong analytical and problem-solving skills with understanding of AI/ML techniques.

Preferred Qualifications:

• Experience deploying Gen AI solutions at scale.
• Experience fine tuning LLMs, SLMs, teacher-student frameworks and model distillation.
• Familiarity with human in the loop methods for aligning LLMs with human preferences.
• Familiarity with agentic framework platforms and concepts. Experience deploying agentic-based solutions is a plus.