Associate 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.

AI/ML team at Prudential Financial is looking for an 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, looking for a full-stack engineer with a deep understanding of data science and software engineering practices.

Responsibilities:

• Strong computer science fundamentals such as algorithms, data structures, multithreading, object-oriented development, distributed applications, client-server architecture
• Basic understanding of deep learning, NLP recommendation systems, and data mining experience with machine learning frameworks such as Scikit Learn, TensorFlow, PyTorch or MXNetExpert
• Implement Machine learning models and data ingestion pipelines.
• Develop and support a platform that enables data scientists to rapidly develop, train, and experiment with machine learning models
• Create and maintain optimal data pipeline architecture by assembling large, complex data sets to meet functional and non-functional business requirements
• Identify and implement internal process improvements, including automating manual processes, optimizing data delivery, and redesigning infrastructure for greater scalability
• Support the building of machine learning, data platforms, and infrastructure required for optimal data extraction, transformations, and loading of data from a wide variety of data sources
• Work with senior ML engineers to identify and solve complex machine learning problems
• Experience in Container, streaming and messaging technologies is a plus
• Implement Machine Learning (ML) and Big Data platforms in Hybrid and multi-cloud environments, specifically in the AWS SageMaker ecosystem

Skills / Qualifications:

• ·Bachelor's degree in computer science, data science, mathematics, or a related field. Master's degree preferred
• Minimum two years experience as a machine learning engineer
• Advanced proficiency with Python framework, Java, and Scala
• Good understanding of mathematics, statistics, and algorithms
• Excellent analytical and problem-solving abilities
• Excellent communication and collaboration skills.