Service Delivery Center, AI & Data, Machine Learning Engineer (MLE) - Analyst
About the role
The Financial Services Operations (FSO) team at EY is dedicated to helping financial institutions build smarter and more efficient operations through data and AI. This role involves working with diverse teams to deliver AI and data services, focusing on designing, building, and maintaining production-grade machine learning and deep learning models.
Responsibilities
- Collaborate with diverse teams to deliver a wide range of AI and data services.
- Work with structured and unstructured data sets to build predictive models and assist clients in making data-driven decisions.
- Apply advanced analytical and statistical methods, including machine learning and data structure design.
- Design and develop solutions using big data technology like Hadoop, Spark, and cloud-based AI services such as AWS SageMaker, Google AI Platform, or Azure Machine Learning.
- Deploy and manage AI applications in the cloud using containerization and orchestration technologies like Docker and Kubernetes.
- Develop and apply data analysis algorithms, including data mining, statistics, machine learning, natural language processing, and others.
- Build and maintain production-grade ML and DL models, machine learning workflows, and pipelines.
- Communicate effectively with internal clients and stakeholders.
- Travel up to 25% of the time.
Requirements
- Bachelor's or Master’s degree in computer science, information systems, or related technology fields.
- At least 1 year of related work experience in AI/ML engineering or MLE/ML Ops.
- Proficiency in Python programming and associated machine learning libraries/packages (sklearn, TensorFlow, PyTorch, etc).
- Experience with cloud-based AI services and machine learning platforms such as AWS SageMaker, Google AI Platform, or Azure Machine Learning.
- Familiarity with containerization and orchestration technologies (Docker, Kubernetes) for deploying and managing AI applications in the cloud.
- Good written and verbal communication skills.
- A willingness and ability to travel at 0%-25%.
Qualifications
- Strong technical capabilities in machine learning and data science.
- Experience with neural network architectures, particularly in areas like natural language processing, computer vision, and machine intelligence.
- Knowledge of ethical implications of generative AI and a commitment to responsible AI practices.
Skills
- Certification in any database management system, reporting, or data visualization, or programming/statistical language.
- Working knowledge or certifications in cloud technologies such as Snowflake, Databricks, AWS, or Azure.
- Experience with generative AI models and techniques, including GANs and Transformers.
Benefits
Competitive compensation package, including a base salary range of $46,700 to $95,200 in all geographic locations in the US, and $56,000 to $108,100 in the New York City Metro Area, Washington State, and California (excluding Sacramento). Additional benefits include medical and dental coverage, pension and 401(k) plans, and a range of paid time off options.
Pay
$46,700 to $95,200 in all geographic locations in the US, and $56,000 to $108,100 in the New York City Metro Area, Washington State, and California (excluding Sacramento).
Schedule
Hybrid model with most people in external, client serving roles expected to work together in person 40-60% of the time over the course of an engagement, project, or year. Employees are granted time off for designated EY Paid Holidays, Winter/Summer breaks, Personal/Family Care, and other leaves of absence when needed to support their physical, financial, and emotional well-being.