Lead Machine Learning Engineer
Apply NowCompany: Prudential Financial
Location: Newark, NJ 07104
Description:
Job Classification:
Technology - Data Analytics & Management
Lead Machine Learning Engineer (The Prudential Insurance Company of America, Newark, NJ):
Responsible for model deployment, algorithm selection, feature engineering, model interpretability, maintenance, and compliance in collaboration with data scientists to help productionize machine learning models at scale. Steer machine learning initiatives from conception to full-scale production. Foster robust relationships with business partners and cross-functional application teams, including DevOps, cloud engineering and platform team. Architect, design, code and deploy machine learning models to cloud environment using preprocessing and training scripts provided by data scientists, ensuring strict adherence to enterprise coding standards. Forge processes, establish model monitoring practices and implement a governance framework to ensure the successful operationalization of models. Deliver essential model training and inference components, frameworks, services using ML Cloud Services ex. AWS Sagemaker. Leverage and optimize end to end model development life cycle (MDLC), Jenkins based CI/CD/CT pipelines, AWS Sagemaker pipeline. Architect and refine training and inference data pipelines, data flow, and data collection strategies for cross-functional teams, assembling extensive and intricate datasets to fulfill business requirements. Collaborate closely with data architects and design teams to resolve technical issues. Innovate and support platform feature development that empowers data scientists to accelerate model research, training, and development. Manage decommissioning of on-premises and AWS-based models following industry best practices to meet business and compliance requirements. Provide ongoing support for models deployed in production by delivering critical hotfixes or enhancements as required.
Telecommuting permitted up to 100%. Candidate may reside and work from anywhere in the U.S.
Full time employment, Monday - Friday, 40 hours per week.
MINIMUM REQUIREMENTS:
Master's degree in Applied Computer Science or a related field and 5 years of related work experience; OR a Bachelor's degree in Applied Computer Science or a related field and 7 years of progressive, post-baccalaureate related work experience.
Of the required experience, must have 5 years of experience in training inference data pipelines and infrastructure required for optimal feature engineering, data extraction and data transformations, and loading data from a wide variety of data sources.
Of the required experience, must have 4 years of experience in supporting building of machine learning systems; and
Of the required experience, must have 3 years of experience in each of the following:
Of the required experience, must have 2 years of experience Utilizing C++, Unix or SQL.
TO APPLY: Please click "Apply" Button. Should you have any difficulty in applying for this position through our website, please contact Ramona.wallace@prudential.com for assistance in the application process.
What we offer you:
Eligibility to participate in a discretionary annual incentive program is subject to the rules governing the program, whereby an award, if any, depends on various factors including, without limitation, individual and organizational performance. To find out more about our Total Rewards package, visit Work Life Balance | Prudential Careers. Some of the above benefits may not apply to part-time employees scheduled to work less than 20 hours per week.
Prudential Financial, Inc. of the United States is not affiliated with Prudential plc. which is headquartered in the United Kingdom.
Prudential is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, ancestry, sex, sexual orientation, gender identity, national origin, genetics, disability, marital status, age, veteran status, domestic partner status, medical condition or any other characteristic protected by law.
If you need an accommodation to complete the application process, please email accommodations.hw@prudential.com.
If you are experiencing a technical issue with your application or an assessment, please email careers.technicalsupport@prudential.com to request assistance.
Technology - Data Analytics & Management
Lead Machine Learning Engineer (The Prudential Insurance Company of America, Newark, NJ):
Responsible for model deployment, algorithm selection, feature engineering, model interpretability, maintenance, and compliance in collaboration with data scientists to help productionize machine learning models at scale. Steer machine learning initiatives from conception to full-scale production. Foster robust relationships with business partners and cross-functional application teams, including DevOps, cloud engineering and platform team. Architect, design, code and deploy machine learning models to cloud environment using preprocessing and training scripts provided by data scientists, ensuring strict adherence to enterprise coding standards. Forge processes, establish model monitoring practices and implement a governance framework to ensure the successful operationalization of models. Deliver essential model training and inference components, frameworks, services using ML Cloud Services ex. AWS Sagemaker. Leverage and optimize end to end model development life cycle (MDLC), Jenkins based CI/CD/CT pipelines, AWS Sagemaker pipeline. Architect and refine training and inference data pipelines, data flow, and data collection strategies for cross-functional teams, assembling extensive and intricate datasets to fulfill business requirements. Collaborate closely with data architects and design teams to resolve technical issues. Innovate and support platform feature development that empowers data scientists to accelerate model research, training, and development. Manage decommissioning of on-premises and AWS-based models following industry best practices to meet business and compliance requirements. Provide ongoing support for models deployed in production by delivering critical hotfixes or enhancements as required.
Telecommuting permitted up to 100%. Candidate may reside and work from anywhere in the U.S.
Full time employment, Monday - Friday, 40 hours per week.
MINIMUM REQUIREMENTS:
Master's degree in Applied Computer Science or a related field and 5 years of related work experience; OR a Bachelor's degree in Applied Computer Science or a related field and 7 years of progressive, post-baccalaureate related work experience.
Of the required experience, must have 5 years of experience in training inference data pipelines and infrastructure required for optimal feature engineering, data extraction and data transformations, and loading data from a wide variety of data sources.
Of the required experience, must have 4 years of experience in supporting building of machine learning systems; and
Of the required experience, must have 3 years of experience in each of the following:
- Deploying large scale machine learning models to production;
- Working with data scientists, enterprise architecture, data engineering design, AIML platform and risk & compliance teams to deploy model to production/cloud environment specifically AWS Sagemaker; and
- Utilizing Python.
Of the required experience, must have 2 years of experience Utilizing C++, Unix or SQL.
TO APPLY: Please click "Apply" Button. Should you have any difficulty in applying for this position through our website, please contact Ramona.wallace@prudential.com for assistance in the application process.
What we offer you:
- 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 Programsincluding 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.
Eligibility to participate in a discretionary annual incentive program is subject to the rules governing the program, whereby an award, if any, depends on various factors including, without limitation, individual and organizational performance. To find out more about our Total Rewards package, visit Work Life Balance | Prudential Careers. Some of the above benefits may not apply to part-time employees scheduled to work less than 20 hours per week.
Prudential Financial, Inc. of the United States is not affiliated with Prudential plc. which is headquartered in the United Kingdom.
Prudential is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, ancestry, sex, sexual orientation, gender identity, national origin, genetics, disability, marital status, age, veteran status, domestic partner status, medical condition or any other characteristic protected by law.
If you need an accommodation to complete the application process, please email accommodations.hw@prudential.com.
If you are experiencing a technical issue with your application or an assessment, please email careers.technicalsupport@prudential.com to request assistance.