AI & Machine Learning Engineering Consultant - Manager - Consulting - Location OPEN

EY•Hartford, DC

42d•$125,500 - $261,600

About The Position

EY’s AI, Data & Engineering team applies emerging technologies and techniques to help clients solve complex problems. This role involves substantial client interaction and collaboration with interdisciplinary teams, with opportunities to research, develop knowledge, and shape innovative approaches across client projects. As a Manager in Model Engineering, you will research, build, and implement scalable AI, machine learning, generative AI, and agentic systems tailored to business requirements across cloud and on-premises environments. You will help design and build solutions that unify, enrich, and derive insights from varied data sources; enhance data pipelines and storage; and ensure data is clean, accurate, and optimized for XOps processes. You will guide technical development and ensure AI solutions are responsibly engineered, evaluated, deployed, maintained, and continuously improved to support client business needs. The role includes leading AI workstreams from solution design through production deployment and optimization, managing multidisciplinary teams, working directly with clients, and identifying opportunities for additional services while managing engagement economics. The position is available anywhere in the country. Travel for client engagements is expected as needed.

Requirements

Bachelor’s degree (four-year degree).
6–10 years of relevant full-time experience in AI, data science, and/or machine learning.
2–4 years of experience directly managing technical teams.
Strong Python skills.
Ability to lead, collaborate, and communicate effectively with diverse, hybrid, and global teams.
Experience designing, building, and maintaining high-impact, high-value production AI/ML solutions on a major cloud platform.
Proficiency in foundation models, generative AI, and agentic AI frameworks, such as OpenAI, DALL·E, LangChain, and retrieval-augmented generation (RAG), and experience with ML packages such as scikit-learn and PyTorch.
Experience with natural language processing and deep learning.
Extensive experience with DevOps tools including Git and Azure DevOps, Agile methodologies including Jira, and CI/CD pipelines for developing, deploying, and scaling analytical solutions.
Experience with MLOps, LLMOps, AgentOps, and ML workflows, including data ingestion, transformation, and evaluation.
Experience with model retraining and feedback-loop methodologies.
Experience with model and solution evaluation, observability, monitoring, and reporting.
Understanding of data structures, data modeling, software engineering, and Responsible AI practices.
Strong foundation in mathematics, statistics, and operations research, with proficiency in data manipulation tools such as SQL, Pandas, and Spark and in deep learning techniques.
Excellent communication skills for conveying findings and recommendations, and willingness to travel for client engagements.
Skills in technical design optimization.
Strong relationship-building skills and demonstrated ability to establish client trust and deliver value.
Digital fluency and emotional agility.
Commercial acumen and negotiation skills.
Proven ability to develop solutions to complex problems and recommend changes to policies and procedures.
Strong judgment in selecting methods and techniques to obtain results.
Experience managing client relationships and delivering high-quality service.
Proven ability to lead teams and manage change.

Nice To Haves

Ability to teach concepts, tools, features, functions, and benefits of different approaches and how to apply them.
Master’s degree in computer science, mathematics, physical sciences, or another quantitative field.
Experience working with diverse teams to deliver complex solutions.
Strong skills in programming languages beyond Python, such as R, JavaScript, Java, C++, or C.
Experience fine-tuning generative AI models.
Experience managing complex projects with multiple stakeholders.
Strong understanding of industry trends and emerging technologies.
Skills in data visualization and storytelling with data.
Experience with image processing techniques and/or speech and audio processing and analysis.

Responsibilities

Lead AI workstreams from solution design through production deployment and ongoing optimization.
Research and implement scalable AI, machine learning, generative AI, and agentic systems for business requirements across cloud and on-premises environments.
Design and build solutions that unify, enrich, and derive insights from varied data sources.
Enhance data pipelines and storage, ensuring data is clean, accurate, and optimized for XOps processes.
Monitor and evaluate learning processes and models to improve performance.
Guide technical development and ensure AI solutions are responsibly engineered, evaluated, deployed, and maintained.
Continuously improve processes by identifying innovative solutions through research and analysis.
Manage multidisciplinary teams delivering complex AI engineering initiatives, with accountability for quality, responsible deployment, and results.
Engage with clients, participate in daily working sessions, and lead workstreams from planning through execution to closure.
Collaborate with data and analytics professionals to industrialize analysis into effective analytics solutions.
Identify opportunities for additional services and manage engagement economics.
Provide technical guidance and share knowledge with team members.
Deliver quality client services on complex, judgmental, or specialized issues involving emerging technology.