AI/ML Engineer

Job Role/Job Description (Please fill in the exact role expected out of the candidate)

What roles and responsibilities will be performed by the selected candidate?

• Seeking a highly experienced and technically adept AI/ML Engineer to spearhead a strategic initiative focused on analyzing annual changes in IRS-published TRCs and identifying their downstream impact on codebases.
  
• Role demands deep expertise in machine learning, knowledge graph construction, and software engineering processes.
  
• The ideal candidate will have a proven track record of delivering production-grade AI solutions in complex enterprise environments.
  

Key Responsibilities:

• Design and development of an AI/ML-based system to detect and analyze differences in IRS TRC publications year-over-year.
  
• Implement knowledge graphs to model relationships between TRC changes and impacted code modules.
  
• Collaborate with tax domain experts, software engineers, and DevOps teams to ensure seamless integration of the solution into existing workflows.
  
• Define and enforce engineering best practices, including CI/CD, version control, testing, and model governance.
  
• Drive the end-to-end lifecycle of the solution—from data ingestion and model training to deployment and monitoring.
  
• Ensure scalability, performance, and reliability of the deployed system in a production environment.
  
• Mentor junior engineers and contribute to a culture of technical excellence and innovation.
  

Required Skills & Experience:

• 8+ years of experience in software engineering, with at least 5 years in AI/ML solution delivery.
  
• Strong understanding of tax-related data structures, especially IRS TRCs, is a plus.
  
• Expertise in building and deploying machine learning models using Python, TensorFlow/PyTorch, and ML Ops frameworks.
  
• Hands-on experience with Knowledge graph technologies (e.g., Neo4j, RDF, SPARQL, GraphQL).
  
• Deep familiarity with software architecture, microservices, and API design.
  
• Experience with NLP techniques for document comparison and semantic analysis.
  
• Proven ability to lead cross-functional teams and deliver complex projects on time.
  
• Strong communication and stakeholder management skills.
  

Preferred Qualifications:

• Experience working on regulatory or compliance-driven AI applications.
  
• Familiarity with code analysis tools and static/dynamic code mapping techniques.
  
• Exposure to cloud platforms (Azure, AWS, GCP) and containerization (Docker, Kubernetes).
  
• Contributions to open-source AI/ML or graph-based projects.
  

Skill Set Required

Must Have

Good to Have

1

AI/ML

Yes

2

Python, TensorFlow/PyTorch, and ML Ops frameworks

Yes

3

Knowledge graph technologies

Yes

4

Data migration testing

Yes

5

Azure DevOps

Yes

6

Azure AI

Yes

7

US Tax understanding

Yes