The AI/ML Engineer designs and builds experimental systems to evaluate emerging AI technologies and guide foundational technical decisions at ITJ. This position will apply machine learning engineering, software prototyping, and modern AI integration techniques to assess frameworks, tools, and patterns in real-world contexts. The best candidate for this position will help the team explore, test, and refine new approaches to delivering intelligent systems across the business. The ideal candidate should have experience developing ML-powered applications in cloud environments, working across the stack from model integration to deployment. The prototypes and tools developed by this team inform platform strategy and are designed to accelerate adoption through reusable, modular patterns. This position can be fully remote. 

• Design and execute machine learning experiments to evaluate emerging AI technologies and frameworks. 
• Prototype and assess end-to-end AI solutions to inform product and platform strategy. 
• Formulate hypotheses and conduct structured evaluations to compare technical approaches. 
• Apply modern ML engineering practices to build and test scalable, modular proof-of concept systems. 
• Contribute to the definition of best practices for experimentation, evaluation, and technical decision-making. 
• Synthesize and communicate experimental results to guide investment and adoption decisions. 
• Translate new research ideas and tools into functional, decision-relevant demonstrations. 
• Operate independently while contributing to a highly collaborative team environment. 
• Communicate technical findings clearly and concisely to both technical and non technical audiences. 
• Show initiative in solving open-ended technical challenges with creativity and rigor.
• Maintain clear documentation and contribute to shared knowledge within the team. 
• Uphold company mission and values through accountability, innovation, integrity, quality, and teamwork. 
• Support and comply with the company’s Quality Management System policies and procedures. 

• Bachelor’s degree in computer science, data science, information technology, statistics, economics, or a related STEM field.  
• 3+ years of experience building machine learning-powered applications or tooling. 
• Strong proficiency in Python and familiarity with modern ML/AI libraries (e.g., PyTorch, Hugging Face, OpenAI SDKs). 
• Experience working with LLM orchestration or agent frameworks. 
• Understanding of model tuning, prompt engineering, or retrieval-augmented generation (RAG) patterns. 
• Experience developing and deploying applications in cloud environments (e.g., AWS, GCP, or Azure), including use of Docker and/or Kubernetes. 
• Demonstrated ability to independently prototype, test, and iterate on technical ideas.
• Familiarity with ML evaluation techniques and structured experimentation workflows.
• Proficiency with version control systems, CI/CD practices, and ML observability tools.