AI/ML Engineering Lead

Role: AI/ML Engineering Lead

Location:

Experience:

Role Overview:

Key Responsibilities:

• Lead the design and development of an AI/ML-based system to detect and analyze differences in IRS TRC publications year-over-year.

• Architect and 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:

• 10+ 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