Lead, Machine Learning Engineer

About the role

The Global Technology team at Prudential is dedicated to driving digital transformation and innovation. As a Lead, Machine Learning Engineer, you will collaborate with Data Scientists, Data Engineers, and Data Analysts to implement machine learning models that enhance stability, productivity, scalability, and integration across various products and services.

Responsibilities

• Operate ML software models and components to solve real-world business problems, working closely with the Product and Data Science teams.
• Develop and validate ML models, automate tests, and deploy applications.
• Leverage cloud-based architectures and technologies to optimize ML models for scale.
• Create optimized data pipelines to feed ML models.
• Implement continuous integration and continuous deployment practices, including test automation and monitoring.
• Collaborate with the Product and Data Science teams to operationalize ML software models and components.
• Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment.
• Implement capabilities to solve sophisticated business problems, deploying innovative products, services, and experiences to delight our customers.

Requirements

• Bachelor of Computer Science or Engineering or equivalent experience.
• Experience with agile development methodologies and Test-Driven Development (TDD).
• Strong understanding of relevant and emerging technologies, ability to coach team members, and a continuous learning focus.
• Advanced technical expertise and experience with machine learning, deep learning, and related technologies.
• Experience with programming languages such as Python, R, SQL, Java, or Scala.
• Knowledge of business concepts, tools, and processes necessary for decision-making within the company.
• Excellent problem-solving, communication, and collaboration skills.

Qualifications

• Advanced technical expertise and experience with machine learning, deep learning, and related technologies.
• Experience with agile development methodologies and Test-Driven Development (TDD).
• Strong understanding of relevant and emerging technologies, ability to coach team members, and a continuous learning focus.
• Advanced Experience and/or Expertise with several of the following software engineering & system design areas:
• Requirement analysis, coding, and testing, version control, microservices architecture, building RESTful APIs, distributed computing, architecture patterns, general understanding of computer architecture, object-oriented programming concepts.
• Advanced Experience and/or Expertise with several of the following machine learning and deep learning areas:
• Good understanding of ML algorithms like linear regression, logistic regression, etc., supervised, unsupervised, and reinforcement learning, AI Frameworks like TensorFlow, PyTorch, scikit-learn etc., neural network, NLP, computer vision, and predictive analytics.
• Advanced Experience and/or Expertise with several of the following model performance management areas:
• model monitoring, model validation, bias detection, explainability, performance, drift, outliers etc.
• Advanced Experience and/or Expertise with several of the following model deployment areas:
• Thorough Understanding of MDLC (Model Development Life Cycle), CI/CD/CT pipelines (using tools like Jenkins, CloudBees, Harness etc.), A/B testing. Pipeline frameworks like MLFlow, AWS SageMaker pipeline etc., model and data versioning.
• Advanced Experience and/or Expertise with several of the following data integration, transformation & processing areas:
• Transforming and mapping raw data to generate insights. Data wrangling through various tools. Understanding big data ecosystems, relational, NOSQL and graph databases, unstructured and semi-structured data. Data processing on distributed systems with Spark/PySpark.
• Advanced Experience and/or Expertise with several of the following statistics and computing areas:
• Strong knowledge of Linear Algebra, Probability and Statistics, Multivariate Calculus, Distributions like Poisson, Normal, Binomial etc.
• Advanced Experience and/or Expertise with several of the following programming languages:
• Python, R, SQL, Java or Scala, SQL.

Skills

• Advanced technical expertise and experience with machine learning, deep learning, and related technologies.
• Experience with agile development methodologies and Test-Driven Development (TDD).
• Strong understanding of relevant and emerging technologies, ability to coach team members, and a continuous learning focus.
• Advanced Experience and/or Expertise with several of the following software engineering & system design areas:
• Requirement analysis, coding, and testing, version control, microservices architecture, building RESTful APIs, distributed computing, architecture patterns, general understanding of computer architecture, object-oriented programming concepts.
• Advanced Experience and/or Expertise with several of the following machine learning and deep learning areas:
• Good understanding of ML algorithms like linear regression, logistic regression, etc., supervised, unsupervised, and reinforcement learning, AI Frameworks like TensorFlow, PyTorch, scikit-learn etc., neural network, NLP, computer vision, and predictive analytics.
• Advanced Experience and/or Expertise with several of the following model performance management areas:
• model monitoring, model validation, bias detection, explainability, performance, drift, outliers etc.
• Advanced Experience and/or Expertise with several of the following model deployment areas:
• Thorough Understanding of MDLC (Model Development Life Cycle), CI/CD/CT pipelines (using tools like Jenkins, CloudBees, Harness etc.), A/B testing. Pipeline frameworks like MLFlow, AWS SageMaker pipeline etc., model and data versioning.
• Advanced Experience and/or Expertise with several of the following data integration, transformation & processing areas:
• Transforming and mapping raw data to generate insights. Data wrangling through various tools. Understanding big data ecosystems, relational, NOSQL and graph databases, unstructured and semi-structured data. Data processing on distributed systems with Spark/PySpark.
• Advanced Experience and/or Expertise with several of the following statistics and computing areas:
• Strong knowledge of Linear Algebra, Probability and Statistics, Multivariate Calculus, Distributions like Poisson, Normal, Binomial etc.
• Advanced Experience and/or Expertise with several of the following programming languages:
• Python, R, SQL, Java or Scala, SQL.

Benefits

• Market competitive base salaries, with a yearly bonus potential at every level.
• Medical, dental, vision, life insurance, disability insurance, Paid Time Off (PTO), and leave of absences, such as parental and military leave.
• 401(k) plan with company match (up to 4%).
• Company-funded pension plan.
• Wellness Programs including up to $1,600 a year for reimbursement of items purchased to support personal wellbeing needs.
• Work/Life Resources to help support topics such as parenting, housing, senior care, finances, pets, legal matters, education, emotional and mental health, and career development.
• Education Benefit to help finance traditional college enrollment toward obtaining an approved degree and many accredited certificate programs.
• Employee Stock Purchase Plan: Shares can be purchased at 85% of the lower of two prices (Beginning or End of the purchase period), after one year of service.

Pay

$125,000.00 to $229,700.00

Schedule

N/A