[Hiring] AI & Machine Learning Engineering Consultant @EY

Role Description

Our AI, Data & Engineering team helps apply cutting edge technology and techniques to bring solutions to our clients. As part of that, you'll sit side-by-side with clients and diverse teams from EY to create a well-rounded approach to advising and solving challenging problems, some of which have not been solved before. No two days will be the same, and with constant research and development, you'll find yourself building knowledge that can be applied across a wide range of projects now, and in the future. You'll need to have a passion for continuous learning, stay ahead of the trends, and influence new ways of working so you can position solutions in the most relevant and innovative way for our clients. You can expect heavy client interaction in a fast-paced environment and the opportunity to develop your own career path for your unique skills and ambitions.

In this role, you will research, build, and implement scalable AI, machine learning, generative AI, and agentic systems that learn, reason, and generate outputs tailored to business requirements on Databricks. You will enhance data pipelines and storage on Databricks, ensuring data is clean, accurate, and optimized for XOps processes. Additionally, you will monitor and evaluate learning processes to continuously improve high-performance models, collaborating with other data and analytics professionals to industrialize analysis into effective analytics solutions. You will deliver solutions on Databricks, from data pipelines to agents in production.

Your key responsibilities

• Leading AI workstreams from solution design through production deployment and ongoing optimization, focusing on the Databricks platform.
• Leading teams building data engineering pipelines, AI solutions (machine learning, generative AI, and agentic AI), and the pipelines that support AI solutions on Databricks.
• Continuously improving processes by identifying innovative solutions through research and analysis.
• Managing multidisciplinary teams to deliver complex AI engineering initiatives, with accountability for quality, responsible deployment, and results.
• Engaging actively with clients, participating in daily working sessions, and leading workstreams from planning through execution to closure.
• Designing, building, and governing domain ontologies and semantic models that define business concepts, relationships, and rules for AI solutions, knowledge graphs, and enterprise data products.
• Applying a product-centric development approach by partnering with product, business, data science, and engineering stakeholders to define user needs, prioritize reusable capabilities, and iteratively deliver measurable outcomes across the product lifecycle.
• Identifying opportunities for additional services and managing engagement economics.

Skills and attributes for success

• Translating AI strategy into implementable Model Engineering activities that align with the client’s goals, mission, and vision.
• Leading teams of AI engineers, data engineers, and data scientists in the delivery of production-grade solutions for clients on Databricks.
• Implementing product-centric AI solutions on Databricks, from discovery and roadmap definition through iterative delivery, adoption, and continuous improvement.
• Working across design, build, deploy, and operate phases to deliver production-grade data and AI pipelines, governed business ontologies, and semantic models on Databricks.
• Staying abreast of AI technology trends and providing directional guidance and recommendations around AIOps, MLOps, and AgentOps tools and solutions on Databricks.
• Applying combined business and technical knowledge to develop and execute ModelOps target architecture on Databricks.
• Collaborating with Data Scientists, Data Engineers, Cloud Engineers, and Platform Engineers, DevOps to implement and sustain solutions in the Databricks platform.
• Understanding clients’ overall data, AI and technology landscape and business priorities and success measures.
• Strong team collaboration and experience working with a diverse team in a hybrid model (on site and remote).
• Consistently delivering quality client services.
• Driving high-quality work products within expected timeframes and on budget.
• Solving problems by incorporating data into decision making.

Qualifications

• A Bachelor’s degree required (4-year degree).
• 6-10 years of relevant experience in AI, Data Science, and/or Machine Learning.
• 2-4 years of experience directly managing technical teams.
• 3-4 years of experience building and deploying production AI/ML solutions on the Databricks platform.
• Databricks Certification with a minimum of 1 professional and 1 associate certification.
• Strong skills in Python, PySpark, and/or Scala.
• Experience designing, building, and maintaining high-impact, high-value production AI/ML solutions on a major cloud platform.
• Proficient in foundation models, generative AI, and agentic AI frameworks.
• Experience with natural language processing and deep learning.
• Extensive experience in DevOps tools, AI-driven SDLC, and CI/CD pipelines.
• Strong foundation in mathematics, statistics, and operations research.
• Excellent communication skills for conveying findings and recommendations.

Requirements

• Experience with model retraining and feedback loop methodologies on Databricks.
• Experience with model and solution evaluation, observability, monitoring, and reporting on Databricks.
• Understanding of data structures, data modeling, software engineering, and Responsible AI practices.
• Experience designing, implementing, validating, and maintaining ontologies, taxonomies, knowledge graphs, or semantic data models.
• Strong relationship-building skills.
• Proven ability to lead teams and manage change.

Benefits

• Medical and dental coverage.
• Pension and 401(k) plans.
• A wide range of paid time off options.

Company Description

At EY, we harness our collective strength to empower you to shape your future with confidence through professional growth, personal fulfillment, and an inclusive culture.