Lead AI Solutions Engineer

Charger logistics Inc. is a world- class asset-based carrier with locations across North America. With over 20 years of experience providing the best logistics solutions, Charger logistics has transformed into a world-class transport provider and continue to grow.

As an Lead AI Solutions Engineer, you will work with a cross functional team at the intersection of science, product, and engineering.

Responsibilities:

• Develop zero-to-one concepts for expert systems.
• Systematically discover and test prompt engineering best practices.
• Optimize data sets for prompt development, model training and evaluation.
• Help create and maintain infrastructure required for efficient prompt development.
• Test and assess open-source solutions for LLM application development including orchestration frameworks, tool interfaces, solutions for context management, etc.
• Develop automated techniques for the design and evaluation of AI agents.
• Analyze usage data to gauge the effectiveness of AI solutions and iteratively improve.
• Stay up to date with the latest research and emerging tech for AI Engineering.

Requirements

• Master’s degree in CS/ML/DS or a bachelor's with equivalent experience.
• 7+ years of transferrable experience in natural language processing (NLP).
• Basic familiarity with the architecture and operation of large language models.
• Strong desire to work closely with subject matter experts on real world use cases.
• Active interest in emerging research and industry trends around AI software development.
• Proficiency in python and AI development tools.
• A mindset for good experiment design and evaluation; strong analytical and critical thinking.
• Excellent communication and organization skills.

Preferred Qualifications:

• Experience working on legal AI systems (e.g., for contract analysis, legal research, or drafting).
• Domain knowledge in legal, tax, or accounting. A law degree (J.D.), paralegal experience, etc.
• A portfolio of projects demonstrating creativity and skill building solutions with LLMs.
• Experience developing NLP applications involving NER, information retrieval, text summarization, question answering, or similar.
• Knowledge of MLOps and the end-to-end lifecycle of software applications involving AI models.
  

Benefits

• Competitive Salary
• Healthcare Benefit Package
• Career Growth