AI & Machine Learning Engineering Consultant - Power & Utilities Sector - Manager - Consulting

EY•Hartford, DC

111d•$125,500 - $261,600•Hybrid

About The Position

EY is seeking an AI & Machine Learning Engineering Consultant at the Manager level to join its Artificial Intelligence and Data team. The role researches, builds, and implements scalable AI systems tailored to business requirements across cloud and on-premises environments. It also enhances data pipelines and storage, monitors and evaluates learning processes, and collaborates with data and analytics professionals to industrialize analyses into maintainable solutions. The position involves substantial client interaction and work with interdisciplinary teams to solve complex technical and business problems. Within the Power & Utilities sector, the consultant will help regulated electric, gas, and water utilities apply AI and analytics to areas such as grid and asset reliability, outage prediction and response, capital planning, customer operations, regulatory reporting, and operational efficiency. The role translates utility priorities—including safety, reliability, affordability, and compliance—into scalable solutions, drawing on utility data systems and supporting the transition of AI solutions from pilots to production while addressing governance, audit, cybersecurity, and regulatory requirements. As a Manager in AI Native Engineering, the role provides technical guidance and performs development work while leading workstreams and teams delivering complex initiatives. The consultant works with clients and EY colleagues to design and build scalable solutions that unify, enrich, and derive insights from diverse data sources. The role also contributes to client relationships, service quality, engagement economics, and the identification of additional service opportunities. The position is offered in a flexible, team-led and leader-enabled hybrid model. Most external, client-serving employees are expected to work together in person 40–60% of the time over an engagement, project, or year. Travel for client engagements is expected. The listed base salary is $125,500–$230,200 across US locations, and $150,700–$261,600 in the New York City Metro Area, Washington State, and California excluding Sacramento. Individual pay depends on factors including education, experience, skills, and geography.

Requirements

Bachelor’s degree (four-year degree) required.
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 production AI/ML solutions on a major cloud platform.
Proficiency with generative AI models and frameworks such as OpenAI, DALL-E, and LangChain, and experience with machine-learning packages such as scikit-learn and PyTorch.
Experience with natural language processing and deep learning.
Extensive experience with DevOps tools such as Git and Azure DevOps, Agile methodologies such as Jira, and CI/CD pipelines for developing, deploying, and scaling analytical solutions.
Experience with MLOps and ML workflows, including data ingestion, transformation, and evaluation.
Experience with model retraining and feedback-loop methodologies.
Experience with model and solution monitoring and reporting.
Understanding of data structures, data modeling, and software engineering best practices.
Strong foundation in mathematics, statistics, and operations research; proficiency with data manipulation tools such as SQL, Pandas, and Spark; and knowledge of deep learning techniques.
Excellent communication skills for conveying findings and recommendations, and willingness to travel for client engagements.
Ability to develop solutions to complex problems and recommend policy and procedure changes.
Strong judgment in selecting methods and techniques to obtain results.
Experience managing client relationships and delivering high-quality service.
Ability to lead teams effectively and manage organizational change.
Comfort working in highly regulated environments with governance, documentation, explainability, and model risk management expectations.
Skills in technical design optimization and strong relationship-building skills.
Demonstrated ability to build client trust and deliver value.
Digital fluency, emotional agility, commercial acumen, and negotiation skills.
Proven ability to lead teams and manage change.

Nice To Haves

Experience delivering analytics or AI solutions in asset-intensive environments such as utilities, energy, infrastructure, manufacturing, or transportation.
Familiarity with utility regulatory, compliance, or operational data considerations.
Deep understanding of, and ability to teach, concepts, tools, features, functions, and benefits of different approaches.
Master’s degree in computer science, mathematics, physical sciences, or another quantitative field.
Experience working with diverse teams to deliver complex solutions.
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 and/or speech and audio processing and analysis.
Exposure to Power & Utilities transformation programs such as grid modernization, advanced metering, wildfire mitigation, energy transition, DER integration, or digital operations initiatives.
Experience supporting executive-level decision-making in regulated environments, including preparing materials that may be reviewed by regulators or governing bodies.

Responsibilities

Lead workstream delivery and effectively manage processes and projects.
Identify and research innovative solutions to improve processes.
Manage professional employees and supervise teams delivering complex technical initiatives, with accountability for performance and results.
Engage actively with clients, participate in daily working sessions, and lead workstreams from planning through execution and closure.
Identify opportunities for additional services and manage engagement economics.
Design and deliver AI/ML use cases for Power & Utilities, including asset health and failure prediction, outage detection and restoration optimization, vegetation management analytics, demand and load forecasting, DER forecasting, predictive maintenance, customer operations optimization, and regulatory analytics.
Work with utility data sources such as SCADA, AMI/AMI 2.0, GIS, EAM systems such as Maximo, OMS, CIS, and historian systems, integrating them into modern analytics platforms.
Help utilities move AI solutions from pilots to production while meeting regulatory, audit, cybersecurity, and data governance requirements.
Research, build, and implement scalable AI systems across cloud and on-premises environments.
Enhance data pipelines and storage so data is clean, accurate, and optimized for XOps processes.
Monitor and evaluate learning processes and improve high-performance models.
Provide technical guidance and perform development tasks to ensure data science solutions are engineered and maintained for clients’ ongoing business needs.
Translate regulated utility priorities into scalable AI-enabled solutions, aligning outcomes with safety, reliability, affordability, compliance, governance, and operational realities.
Translate AI and analytics outputs into business-relevant insights for utility executives, regulators, and operational leaders.
Deliver quality client services on complex, judgmental, or specialized emerging-technology issues and communicate findings and recommendations.
Lead teams, manage organizational change, build client relationships, and share technical knowledge with team members.