Lead Machine Learning Engineer

Prudential Financial

Confirmed live yesterday High trust

Quick summary

Work type: On-site
Location: Newark, NJ
Salary: $125,000–$229,700 / yr
Posted: 10 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $219k

This role $177k

$109k most similar roles pay here $273k

This role pays less than 84% of similar roles. Most pay $192,050–$246,150 — the shaded band above. At the midpoint, this role pays about $177k versus about $219k for comparable roles.

Based on 240 similar postings.

Employer

About Prudential Financial

Prudential Financial is a global financial services leader and premier active global investment manager.

Prudential Financial currently has 32 open roles on FindRole.

Listed pay typically runs $123,700–$202,050 across 32 roles with salary data.

Most-posted roles

View all roles at Prudential Financial

At a glance

TL;DR · Lead Machine Learning Engineer

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Lead, Machine Learning Engineer As a Lead, Machine Learning Engineer, you will join the Global Technology team to partner with data scientists and engineers in building scalable machine learning models that ensure product stability and integration. You will be responsible for operationalizing ML software components, writing and testing application code, constructing optimized data pipelines, and automating deployments using CI/CD best practices. The role involves solving complex business problems by leveraging cloud-based architectures and managing the model development lifecycle. You will utilize a technical stack including Python, R, SQL, Java, or Scala, alongside frameworks like TensorFlow, PyTorch, and scikit-learn. Key competencies include experience with microservices, RESTful APIs, Spark/PySpark for distributed processing, and deep knowledge of linear algebra and statistics to deliver high-performing predictive analytics and machine learning solutions within a complex financial services environment.

Skills

Python R SQL Java Scala TensorFlow PyTorch scikit-learn Spark PySpark MLflow AWS SageMaker CI/CD TDD RESTful APIs Microservices NoSQL Graph Databases Machine Learning Deep Learning

What you'll do

Operationalize machine learning models and components to solve real-world business problems.
Write and test application code to develop, validate, and automate the deployment of ML models.
Construct optimized data pipelines to feed machine learning models using various tools and technologies.
Leverage cloud-based architectures to deliver scalable and integrated machine learning solutions.
Implement CI/CD best practices, including automated testing and monitoring, for model and code deployment.
Manage model performance through monitoring, validation, bias detection, and explainability analysis.
Coach team members on emerging technologies and integrate innovation into daily workflows.
Resolve complex technical impediments by analyzing data and evaluating intangible variables to solve business problems.

What we're looking for

Hold a Bachelor of Computer Science, Engineering, or a related field.
Demonstrate advanced expertise in software engineering, system design, and microservices architecture.
Possess deep knowledge of machine learning algorithms, deep learning frameworks like TensorFlow or PyTorch, and predictive analytics.
Exhibit proficiency in model performance management including monitoring, validation, bias detection, and explainability.
Demonstrate experience with Model Development Life Cycle (MDLC) and CI/CD pipelines using tools like Jenkins or MLFlow.
Show expertise in data integration, transformation, and processing within big data ecosystems and distributed systems.
Possess strong knowledge of statistics, linear algebra, probability, and multivariate calculus.
Proficiency in programming languages including Python, R, SQL, Java, or Scala.

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