EY AI & Machine Learning Engineer - Senior Consulting Open Location 

United States, New York, New York 

614915438

Technology – Data and Decision Science – AI Native Engineering
AI/Machine Learning Engineer, Senior Consultant

Our Artificial Intelligence and Data 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.

As a Senior AI Native Engineer, you will be at the forefront of revolutionizing how businesses leverage artificial intelligence. Your role will involve researching, building, and implementing scalable AI systems that learn and make predictions tailored to diverse business environments, whether in the cloud or on-premises. You will enhance data pipelines to ensure data integrity and optimize learning processes, all while collaborating with a talented team of data and analytics professionals.

Your key responsibilities
In this role, you will contribute significantly to the delivery of innovative AI solutions. You will work with a wide variety of clients to deliver the latest data science and big data technologies. Your teams will design and build scalable solutions that unify, enrich, and derive insights from varied data sources across a broad technology landscape. You will help our clients navigate the complex world of modern data science, analytics, and software engineering. We'll look to you to provide guidance and perform technical development tasks to ensure data science solutions are properly engineered and maintained to support the ongoing business needs of our clients.You will spend your time on key responsibilities that include:

• Researching and implementing scalable AI systems that meet business requirements.
• Enhancing data pipelines and storage for optimal data accuracy and cleanliness.
• Monitoring and optimizing learning processes to improve high-performance models.
• This position may have travel requirements as needed to engage with external clients regularly.

Skills and attributes for success
To excel in this role, you will need a blend of technical expertise and interpersonal skills. Your ability to navigate complex challenges and deliver impactful solutions will be essential.

This role will work to deliver tech at speed, innovate at scale and put humans at the center. Provide technical guidance and share knowledge with team members with diverse skills and backgrounds. Consistently deliver quality client services focusing on more complex, judgmental and/or specialized issues surrounding emerging technology. Demonstrate technical capabilities and professional knowledge. Learn about EY and its service lines and actively assess and present ways to apply knowledge and services.

• Strong analytical and decision-making skills to guide project direction.
• Proven experience in project management and tracking deliverable completion.
• Ability to build and maintain relationships with clients and team members.
• Excellent communication skills to convey complex ideas effectively.

To qualify for the role, you must have

• A Bachelor’s degree required (4-year degree).
• 3-6 years of full-time working experience in AI and/or Machine Learning
• Strong skills in Python.
• Experience using Generative AI models and frameworks e.g. OpenAI family, open source LLMs, Dall-e, LlamaIndex, Langchain, Retrieval Augmented Generation (RAG).
• Experience working with popular ML packages such as scikit-learn, Pytorch and ONNX, or related ML libraries.
• Extensive experience using DevOps tools like GIT, Azure Devops and Agile tools such as Jira to develop and deploy analytical solutions with multiple features, pipelines, and releases.
• A solid understanding of Machine Learning (ML) workflows including ingesting, analysing, transforming data and evaluating results to make meaningful predictions.
• Experience with MLOps methods and platforms such as MLFlow.
• Experience with CI/CD and test-driven development.
• Experience designing, building, and maintaining ML models, frameworks, and pipelines.
• Experience designing and deploying end to end ML workflows on at least one major cloud computing platform.
• Understanding of data structures, data modelling and software engineering best practices.
• Proficiency using data manipulation tools and libraries such as SQL, Pandas, and Spark.
• Clearly communicating findings, recommendations, and opportunities to improve data systems and solutions.
• Experience with containerization and scaling models.
• Integrating models and feedback from downstream consumption systems - reporting and dashboards, AI driven applications.
• Proficiency in deep learning techniques.
• Strong foundation in mathematics, statistics, and operations research.
• Experience with machine learning algorithms and data architecture design.
• Familiarity with cloud computing and technical design optimization.
• Knowledge of natural language processing and image processing techniques.
• Understanding of continuous integration and deployment methodologies.
• Experience in scaling models for various applications.
• Strong mathematical and quantitative skills including calculus, linear algebra, and statistics.
• Willingness to travel to meet client obligations.

Ideally, you’ll also have

• Master's degree Computer Science, Mathematics, Physical Sciences, or other quantitative field.
• Experience in hybrid collaboration and emotional agility.
• A track record of working with diverse teams to drive outcomes through complex problem-solving.
• Knowledge of sustainability practices in technology.
• A deep understanding of and ability to teach concepts, tools, features, functions, and benefits of different approaches to apply them.
• Strong skills in languages beyond Python: R, JavaScript, Java, C++, C.
• Experience fine-tuning Generative AI models.