Vice President, Applied AI/ML Lead
Plano, TX, United States
JPMorgan Chase & Co.
As a Vice President, Applied AI/ML Lead in our technology team, you will have the opportunity to solve exciting business problems in the domain of commercial banking, payments, and financial services. You will be expected to have a strong curiosity for data and a proven track record of successfully applying rigorous scientific methods with proficiency in Machine Learning Engineering and DevOps capabilities. This role provides a unique opportunity to apply your skills and have a direct impact on global business.
The ideal candidate will have a strong knowledge of ML, NLP, Deep Learning, Knowledge Graphs and have experience working with massive amounts of data. They should also have strong software engineering skills and the ability to build systems that reach JP Morgan scale. This is a unique opportunity to apply your skills and have a direct impact on global business.
Job Responsibilities
- Build and train production grade ML models on large-scale datasets to solve various business use cases for Commercial Banking.
- Use large scale data processing frameworks such as Spark, AWS EMR for feature engineering and be proficient across various data both structured and un-structured.
- Use Deep Learning models like CNN, RNN and NLP (BERT) for solving various business use cases like name entity resolution, forecasting and anomaly detection.
- Build ML models across Public and Private clouds including container-based Kubernetes environments.
- Develop end-to-end ML pipelines necessary to transform existing applications and business processes into true AI systems.
- Build both batch and real-time model prediction pipelines with existing application and front-end integrations.
- Collaborate to develop large-scale data modeling experiments, evaluating against strong baselines, and extracting key statistical insights and/or cause and effect relations.
Required qualifications, capabilities and skills
- 6+ years of experience with expertise in building and deploying production-grade machine learning (ML) and large language model (LLM) models on large-scale datasets
- Proficiency in leveraging large-scale data processing frameworks like Spark and AWS EMR for feature engineering, working with both structured and unstructured data
- Ability to build ML and LLM models that can be deployed across public and private clouds, including container-based Kubernetes environments like EKS
- Experience in developing end-to-end ML and LLM pipelines to transform existing applications and business processes into AI-powered systems
- Familiarity with building both batch and real-time model prediction pipelines with existing application and front-end integrations
- Expertise in Python, PySpark, and deep learning frameworks like TensorFlow, as well as proficiency in MLOps
- Experience in designing and building highly scalable, distributed ML and LLM models in production, with proficiency in Scala, applied machine learning, and statistical methods
- Knowledge of analytics tools and technologies, such as SQL, Presto, Spark, Python, and the AWS suite
- Familiarity with machine learning techniques and advanced analytics, including regression, classification, clustering, time series, econometrics, causal inference, and mathematical optimization
Preferred qualifications, capabilities and skills:
- Experience working with end-to-end pipelines using frameworks like KubeFlow, TensorFlow, and/or crowd-sourced data labeling
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
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: AWS Banking BERT Causal inference Classification Clustering Deep Learning DevOps Econometrics Engineering Feature engineering Kubeflow Kubernetes LLMs Machine Learning ML models MLOps NLP Pipelines PySpark Python RNN Scala Spark SQL Statistics TensorFlow Unstructured data
Perks/benefits: Career development Competitive pay Health care Wellness
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