Overview
On Site
Full Time
Skills
Google Cloud Platform
Machine Learning (ML)
Data modeling
Application development
Real-time
Programming languages
Time series
Deep learning
scikit-learn
Software engineering
Design patterns
Data structure
Multithreading
Apache Spark
Cloud computing
Big data
Apache Kafka
Version control
Continuous integration
Investment banking
Corporate banking
Asset management
Health care
Management
IMPACT
Training
Python
PySpark
TensorFlow
Machine Learning Operations (ML Ops)
Storage
Network
CNS
Intellectual property
Database
Messaging
Design
Algorithms
Collaboration
Data
Scalability
Optimization
Research
Artificial intelligence
Leadership
Java
PyTorch
Statistics
Amazon Web Services
Microsoft Azure
Apache Hadoop
Docker
Kubernetes
Streaming
Git
JIRA
Software deployment
Continuous delivery
Finance
Banking
Backup
Coaching
Recruiting
SAP BASIS
Law
Job Details
Are you looking for an exciting opportunity to join a dynamic and growing team in a fast paced and challenging area? This is a unique opportunity apply your skills and have a direct impact on global business. You will be building and training production-grade ML models on large-scale datasets, developing end-to-end ML pipelines, and collaborating to develop large-scale data modeling experiments. Your expertise in Python, PySpark, DL frameworks like TensorFlow, and MLOps will be crucial in this role.
As an experienced Machine Learning Engineer, you will work as part of the Storage team within Compute Network Storage(CNS), working with an inspiring and curious team of technologists dedicated to deploying and developing large-scale infrastructure solutions that support JPMorgan Chase & Co's diverse and critical businesses. The Compute Network Storage(CNS) group, within Infrastructure Platforms (IP) is responsible for defining, developing and operating cloud products consumed by our Application Development Partners across the firm. Our Product Portfolio includes Private and Public Cloud Platforms and a wide range of services such as databases, messaging and telemetry.
Job Responsibilities
Design, develop, and implement machine learning algorithms and models to solve specific business problems.
Collaborate with data scientists and domain experts to identify and engineer relevant features for improving model accuracy and robustness.
Deploy machine learning models into production systems, ensuring scalability, reliability, and efficiency.
Work closely with product managers, software engineers, and other stakeholders to understand requirements, prioritize tasks, and deliver ML solutions that meet business objectives.
Implement monitoring and logging mechanisms to track model performance in real-time and address any issues that arise.
Conduct hyper parameter optimization to fine-tune model performance and improve generalization on unseen data.
Research and analyze data sets using a variety of statistical and machine learning techniques
Communicate AI capabilities and results to both technical and non-technical audiences
Document approaches taken, techniques used and processes followed to comply with industry regulation
Collaborate closely with cloud and SRE teams while taking a leading role in the design and delivery of the production architectures for our solutions.
Required Qualifications, Capabilities, And Skills
Proficiency in programming languages such as Python, Java
Strong understanding of machine learning algorithms, including time series algorithms, deep learning, reinforcement learning, and classical ML techniques.
Experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, scikit-learn, etc.
Solid understanding of software engineering principles, including design patterns, data structures, and algorithms.
Track record of developing, deploying business critical machine learning models
Good exposure to ML ecosystem components like Feature Store, Feature Registry and MLOps
Broad knowledge of MLOps tooling - for versioning, reproducibility, observability etc
Experience monitoring, maintaining, enhancing existing models over an extended time period
Solid understanding of fundamentals of statistics, optimization and ML theory. Familiarity with popular deep learning architectures (transformers, CNN, auto encoders etc.)
Hands-on experience in implementing distributed/multi-threaded/scalable applications (incl. frameworks such as Apache Spark, Dask etc.)
Able to communicate technical information and ideas at all levels; convey information clearly and create trust with stakeholders.
Preferred Qualifications, Capabilities, And Skills
Experience with cloud computing platforms such as AWS, Azure, or Google Cloud Platform.
Experience of big data technologies (e.g. Spark, Hadoop, Apache Kafka)
Knowledge of containerization technologies such as Docker and Kubernetes.
Have constructed batch and streaming micro services exposed as REST/gRPC endpoint.
Familiarity with version control systems such as Git and collaboration tools like Jira.
Experience with continuous integration and continuous deployment (CI/CD) pipelines.
About Us
JPMorgan Chase & Co., 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. For those in eligible roles, we offer discretionary incentive compensation which may be awarded in recognition of firm performance and 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 is an Equal Opportunity Employer, including Disability/Veterans
As an experienced Machine Learning Engineer, you will work as part of the Storage team within Compute Network Storage(CNS), working with an inspiring and curious team of technologists dedicated to deploying and developing large-scale infrastructure solutions that support JPMorgan Chase & Co's diverse and critical businesses. The Compute Network Storage(CNS) group, within Infrastructure Platforms (IP) is responsible for defining, developing and operating cloud products consumed by our Application Development Partners across the firm. Our Product Portfolio includes Private and Public Cloud Platforms and a wide range of services such as databases, messaging and telemetry.
Job Responsibilities
Design, develop, and implement machine learning algorithms and models to solve specific business problems.
Collaborate with data scientists and domain experts to identify and engineer relevant features for improving model accuracy and robustness.
Deploy machine learning models into production systems, ensuring scalability, reliability, and efficiency.
Work closely with product managers, software engineers, and other stakeholders to understand requirements, prioritize tasks, and deliver ML solutions that meet business objectives.
Implement monitoring and logging mechanisms to track model performance in real-time and address any issues that arise.
Conduct hyper parameter optimization to fine-tune model performance and improve generalization on unseen data.
Research and analyze data sets using a variety of statistical and machine learning techniques
Communicate AI capabilities and results to both technical and non-technical audiences
Document approaches taken, techniques used and processes followed to comply with industry regulation
Collaborate closely with cloud and SRE teams while taking a leading role in the design and delivery of the production architectures for our solutions.
Required Qualifications, Capabilities, And Skills
Proficiency in programming languages such as Python, Java
Strong understanding of machine learning algorithms, including time series algorithms, deep learning, reinforcement learning, and classical ML techniques.
Experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, scikit-learn, etc.
Solid understanding of software engineering principles, including design patterns, data structures, and algorithms.
Track record of developing, deploying business critical machine learning models
Good exposure to ML ecosystem components like Feature Store, Feature Registry and MLOps
Broad knowledge of MLOps tooling - for versioning, reproducibility, observability etc
Experience monitoring, maintaining, enhancing existing models over an extended time period
Solid understanding of fundamentals of statistics, optimization and ML theory. Familiarity with popular deep learning architectures (transformers, CNN, auto encoders etc.)
Hands-on experience in implementing distributed/multi-threaded/scalable applications (incl. frameworks such as Apache Spark, Dask etc.)
Able to communicate technical information and ideas at all levels; convey information clearly and create trust with stakeholders.
Preferred Qualifications, Capabilities, And Skills
Experience with cloud computing platforms such as AWS, Azure, or Google Cloud Platform.
Experience of big data technologies (e.g. Spark, Hadoop, Apache Kafka)
Knowledge of containerization technologies such as Docker and Kubernetes.
Have constructed batch and streaming micro services exposed as REST/gRPC endpoint.
Familiarity with version control systems such as Git and collaboration tools like Jira.
Experience with continuous integration and continuous deployment (CI/CD) pipelines.
About Us
JPMorgan Chase & Co., 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. For those in eligible roles, we offer discretionary incentive compensation which may be awarded in recognition of firm performance and 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 is an Equal Opportunity Employer, including Disability/Veterans