Lead Machine Learning Engineer

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Scala Programming, R Programming, Large data sets

Job Description

Technology - Software Development/Quality Engineering

Prudential’s Global Technology team is the spark that ignites the power of Prudential for our customers and employees worldwide. Our organization plays a critical and highly visible role in delivering customer-driven solutions across every area of the company. The Global Technology team is made up of diverse, agile-thinking, and highly skilled professionals; we use our combined capabilities to enable the organization with innovation, speed, agility, scalability and efficiency. 

The Global Technology team takes great pride in our culture where digital transformation is built into our DNA. When you join the Global Technology organization at Prudential, you’ll unlock a challenging and impactful career – all while growing your skills and advancing your profession at one of the world’s leading financial services institutions.

Data Tech team at Prudential Financial is looking for a Sr. ML Engineer to join a diverse team dedicated to providing best-in-class data services to our customers, stakeholders, and partners.

As a part of our CDO organization, you will work with our Data Science and BUs to define solutions for operationalizing data-driven decision making in a cost effective and scalable manner. A full stack engineer with deep understanding of data science and software engineering practices.

Responsibilities:

• Build machine learning pipelines from inception to production: build relationships with business partners and cross-functional teams.
• Develop new platform services and technologies that enable migration of on-prem ML Models to AWS and the eventual decommissioning of on-prem models.
• Design, Develop & deliver critical components, frameworks, services, and products using AWS SageMaker, Lambda, and container technologies in AWS.
• Develop processes, model monitoring, and governance framework for successful ML model operationalization.
• Define standards for engineering and operational excellence for running best-in-class ML platforms and continue to improve ML platforms to keep up with the latest innovations.
• Assist in gathering and analyzing non-functional requirements, and translate that into technical specifications for robust, scalable, supportable solutions that work well within the overall system architecture

Skills / Qualifications:

• 5+ years of software engineering experience and have experience using AWS and Sagemaker
• Bachelor's degree in computer science, computer engineering, or a related engineering field. Master's degree preferred.
• Advanced proficiency with Python and SQL
• Strong computer science fundamentals such as algorithms, data structures, multithreading,
• In-depth experience building solutions using public clouds such as AWS
• Experience using ML platforms like SageMaker, H2O, DataRobot, etc.
• Have knowledge on model performance, confusion matrix, ROC/AUC curve
• Have experience on deploying ML models linvolve regression, classification and neural network models
• Excellent communication and collaboration skills
• AWS certifications are a plus

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