Lead Machine Learning Engineer

Prudential Financial, Inc.
Newark, United States of America
yesterday

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior
Compensation
$ 198K

Job location

Remote
Newark, United States of America

Tech stack

Artificial Intelligence
Azure
Information Systems
Computer Engineering
Data Cleansing
Github
Python
Machine Learning
Object-Oriented Software Development
Software Engineering
Kubernetes
Information Technology
Machine Learning Operations
Docker
Jenkins

Job description

Lead Machine Learning Engineer (The Prudential Insurance Company of America, Newark, NJ):

Design and develop machine learning models and algorithms. Lead the end-to-end ML pipeline, including data preprocessing, model training, evaluation, and deployment. Collaborate with cross-functional teams to integrate ML solutions into products. Research and implement state-of-the-art ML techniques. Mentor junior engineers and guide technical decisions. Ensure scalability, performance, and reliability of ML systems. Monitor and improve model performance over time. Communicate technical concepts to stakeholders.

Telecommuting permitted up to 100% per week. Candidate may work and reside from anywhere in the U.S.

Requirements

5 years of progressive, post-baccalaureate related work experience.

Minimum Education Required

Bachelor's degree in Computer Science, Computer Engineering, Information Systems, or a related field, Bachelor's degree in Computer Science, Computer Engineering, Information Systems, or a related field, and 5 years of progressive, post-baccalaureate related work experience.

Must have 5 years of experience in:

  • Software engineering;

  • Python, including object-oriented programming;

  • MLOps: Building and maintaining CI/CD pipelines for automating the build, testing, and deployment of ML models;

  • Jenkins, MLFlow, or Github Actions;

  • Packaging models and their dependencies into Docker containers;

  • Using Kubernetes to deploy, scale, and manage containerized applications; and

  • ML algorithms: Linear models and tree-based models.

Must have 2 years of experience in using cloud platforms for deploying and managing ML models: SageMaker, Bedrock, Azure AI, Foundry, or Vertex AI.

Domestic travel required up to 10%.

Benefits & conditions

$197,700.00 / Yearly

Hours Per Week

40

Number Of Positions, Full time employment, Monday - Friday, 40 hours per week, $197,700.00 per year. Benefits incl. medical, dental, PTO & more.

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