AI and Machine Learning Engineer

Join Grant Thornton US as an AI and Machine Learning Engineer, where you'll be tasked with designing and building transformative AI solutions. This role spans various applications, from machine learning models to Generative AI and agent-driven workflows, all while adhering to best practices in software engineering and MLOps/LLMOps. We are hiring across multiple major cities in the U.S.

As an AI and Machine Learning Engineer, your contributions will be vital across the entire project lifecycle: feature engineering, model creation and validation, API/service integration, and ensuring production readiness through versioning, testing, and monitoring with a focus on responsible AI. We are seeking candidates for both Manager (3-4 years of experience) and Director level (5+ years), with the expectation that Managers will lead small projects and mentor teammates, while Directors will set technical benchmarks and enhance our existing frameworks and accelerators. Ideal candidates will possess a curiosity for innovation, an ability to navigate ambiguous client environments, and a passion for developing AI solutions that are accurate, secure, and production-ready. This is an exciting opportunity to advance our AI capabilities and advisory services.

Key Responsibilities:

• Develop, test, and refine AI solutions across multiple platforms including ML, Generative AI, and workflow automation from the initial prototype to production.
• Create data preparation and feature engineering pipelines; establish training and fine-tuning workflows; execute thorough model evaluations using both offline metrics and human assessments as needed.
• Implement AI-driven services and APIs that support batch and real-time processing with careful attention to request/response regulations, latency impacts, and enterprise system integration.
• Prioritize software engineering best practices, focusing on code quality, testing (unit and integration), version control, proper packaging, and comprehensive documentation.
• Apply MLOps/LLMOps methodologies: manage experiments, models, prompts, and versioning while ensuring reproducibility and implementing CI/CD strategies.
• Set up systems for observability with a focus on logging, monitoring, analytics, cost tracking, and incident management.
• Embed responsible AI practices ensuring proper data governance, security measures, and output integrity.
• Work closely with Solution Architects and key client stakeholders to clearly define project requirements, demonstrate progress, manage project trade-offs, and achieve measurable results.
• Lead specific workstreams, support team members, conduct code and design evaluations, and promote the development of reusable frameworks and accelerators.

Qualifications

• Bachelor's degree in Computer Science, Data Science, Engineering, or a related field.
• 5+ years (Manager level) or 7+ years (Director level) of hands-on experience in delivering practical AI solutions in either production or production-like settings.
• Strong expertise in Python and experience in crafting production-level services, with solid grounding in data structures, testing, and debugging techniques.
• Demonstrated experience in machine learning development including feature engineering, model training, evaluation, and inference using tools such as scikit-learn, XGBoost, PyTorch, or TensorFlow.
• Knowledge of Generative AI principles, particularly methodologies like RAG (retrieval, chunking, embeddings, reranking) and LLM evaluation metrics (quality, safety checks, hallucination assessments).
• Understanding of MLOps/LLMOps fundamentals: version management, experimental tracking, CI/CD principles, deployment strategies, and monitoring mechanisms.
• Familiarity with data engineering practices and modern data platforms (preferably SQL and Spark; experience with data lakes/warehouses like Snowflake, Databricks, or BigQuery is a plus).
• Experience working with cloud environments (AWS, Azure, or GCP) and understanding enterprise constraints around networking and identity management.
• Excellent communication skills for liaising with clients and documenting decision-making processes.
• Prior experience in consulting or an internal consulting role is valued.
• This position requires in-person attendance at least two days a week either at a Grant Thornton office or at a client site.
• Willingness to travel up to 40% as needed.
• Must be eligible to work in the United States; this role does not offer employer sponsorship.

About Grant Thornton:

At Grant Thornton, we strive to make business personable and foster trust in every outcome—both for our clients and our employees. Our approach exceeds standard expectations in professional services by offering a career path that emphasizes opportunity, flexibility, and support. This commitment to individuality drives our continued success.

Our U.S. presence operates through two main entities: Grant Thornton LLP, a leading CPA firm providing audit and assura