Overview
On Site
Full Time
Skills
FOCUS
Artificial Intelligence
Software Development
Machine Learning Operations (ML Ops)
Workflow
Performance Metrics
A/B Testing
Collaboration
Research
Prototyping
Evaluation
Python
TensorFlow
PyTorch
scikit-learn
Training
Amazon SageMaker
Electronic Health Record (EHR)
Amazon S3
Data Lake
Meta-data Management
Continuous Integration
Continuous Delivery
Jenkins
Bitbucket
Kubernetes
Data Processing
Apache Spark
Distributed Computing
Grafana
Cloud Computing
Computer Science
Amazon Web Services
Machine Learning (ML)
Agile
Investment Banking
Corporate Banking
Banking
Asset Management
Health Care
Backup
Coaching
Recruiting
SAP BASIS
Law
Finance
Human Resources
Marketing
Job Details
Job Description
We build machine learning applications that integrate with other applications throughout the firm including workforce tech and HR functions. Our current focus is building a workforce tech AI/ML platform for HR portfolio. Machine Learning models add business critical information to various HR functions like employee experience, recruiting, surveys etc. and our platform integrates with a number of internal applications serving thousands of business users.
As Machine Learning Software Engineer, you will apply your depth of knowledge and expertise to all aspects of the Machine Learning software development lifecycle, as well as partner continuously with your many stakeholders on a daily basis to stay focused on common goals. We embrace a culture of experimentation and constantly strive for improvement and learning.
Job responsibilities
Deploy machine learning models in production environments using MLOps best practices
Implement and optimize ML pipelines for training, evaluation, and inference on distributed systems in AWS cloud (SageMaker, ECS)
Architect and develop data processing workflows to handle large-scale datasets for machine learning applications
Build and maintain scalable ML infrastructure with monitoring, versioning, and automated retraining capabilities
Develop robust model evaluation frameworks to measure and track model performance metrics
Implement A/B testing frameworks for ML model deployment and validation
Collaborate with data scientists to translate research prototypes into production-ready ML systems
Required qualifications, capabilities, and skills
Proven experience (3+ years) as a Machine Learning Engineer with a track record of deploying ML models to production
Expert-level experience in ML development lifecycle including data preparation, feature engineering, model training, evaluation, and deployment
Advanced proficiency in Python for ML development using frameworks such as TensorFlow, PyTorch, scikit-learn, or similar
Demonstrated experience implementing and optimizing ML pipelines in AWS SageMaker, including model training, hyperparameter tuning, and deployment
Hands-on experience with AWS ML services including SageMaker, EMR, Lambda, CloudWatch, and S3 Data Lake architecture (this is a must)
Experience with ML model versioning, experiment tracking, and ML metadata management tools and Strong knowledge in ML-specific CI/CD pipelines using tools such as Jenkins, Spinnaker, Bitbucket, and MLflow (this is a must)
Experience containerizing ML applications and deploying them on Kubernetes in AWS environment and Proficiency in data processing at scale using Spark, Dask, or similar distributed computing frameworks, in addition experience with ML monitoring and observability tools such as Prometheus, Grafana, or Cloud Watch.
Preferred qualifications, capabilities, and skills
About Us
JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world's most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.
We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans
About the Team
Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we're setting our businesses, clients, customers and employees up for success.
We build machine learning applications that integrate with other applications throughout the firm including workforce tech and HR functions. Our current focus is building a workforce tech AI/ML platform for HR portfolio. Machine Learning models add business critical information to various HR functions like employee experience, recruiting, surveys etc. and our platform integrates with a number of internal applications serving thousands of business users.
As Machine Learning Software Engineer, you will apply your depth of knowledge and expertise to all aspects of the Machine Learning software development lifecycle, as well as partner continuously with your many stakeholders on a daily basis to stay focused on common goals. We embrace a culture of experimentation and constantly strive for improvement and learning.
Job responsibilities
Deploy machine learning models in production environments using MLOps best practices
Implement and optimize ML pipelines for training, evaluation, and inference on distributed systems in AWS cloud (SageMaker, ECS)
Architect and develop data processing workflows to handle large-scale datasets for machine learning applications
Build and maintain scalable ML infrastructure with monitoring, versioning, and automated retraining capabilities
Develop robust model evaluation frameworks to measure and track model performance metrics
Implement A/B testing frameworks for ML model deployment and validation
Collaborate with data scientists to translate research prototypes into production-ready ML systems
Required qualifications, capabilities, and skills
Proven experience (3+ years) as a Machine Learning Engineer with a track record of deploying ML models to production
Expert-level experience in ML development lifecycle including data preparation, feature engineering, model training, evaluation, and deployment
Advanced proficiency in Python for ML development using frameworks such as TensorFlow, PyTorch, scikit-learn, or similar
Demonstrated experience implementing and optimizing ML pipelines in AWS SageMaker, including model training, hyperparameter tuning, and deployment
Hands-on experience with AWS ML services including SageMaker, EMR, Lambda, CloudWatch, and S3 Data Lake architecture (this is a must)
Experience with ML model versioning, experiment tracking, and ML metadata management tools and Strong knowledge in ML-specific CI/CD pipelines using tools such as Jenkins, Spinnaker, Bitbucket, and MLflow (this is a must)
Experience containerizing ML applications and deploying them on Kubernetes in AWS environment and Proficiency in data processing at scale using Spark, Dask, or similar distributed computing frameworks, in addition experience with ML monitoring and observability tools such as Prometheus, Grafana, or Cloud Watch.
Preferred qualifications, capabilities, and skills
- Computer science degree or equivalent experience
- AWS Certifications (AWS Solution architect, developer or ML Specialty)
- Agile fundamentals
About Us
JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world's most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.
We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans
About the Team
Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we're setting our businesses, clients, customers and employees up for success.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.