About the role
from listingYou will be part of an energetic A.I./Machine Learning cross-functional team, collaborating with various business/product partners (e.g. Credit, Fraud, Risk, Web, Mobile, Marketing, Enterprise Automation, etc.) to drive a cohesive set of solutions enabling the ever-growing strategic capabilities in the AI field.
Combine A.I./Machine Learning and Technology knowledge to implement highly scalable solutions to solve real-world problems in areas such as Generative AI, Personalization, Image Recognition, Speech Recognition, Natural Language Processing, Best Next Action, and Time Series predictions
Build solutions from identifying business problems, to collecting training dataset, to analyzing data, to modeling, to validating and to delivering production grade solutions at scale.
Research latest related academic papers and test nascent ideas which can potentially solve new business problems and enhance existing solutions.
Responsible for developing and defining deployment strategies for production quality AI solutions in Cloud infrastructure at scale
Drive both high-level and detailed technical designs and conduct design reviews as needed
Responsible for health and quality of the code across the portfolio, including leadership over innovation, functional testing, and CI/CD tool integration
Provide technical mentorship to team members at junior levels
Actively participate in business and technical discussions and forums across Amex
PhD/ Master’s Degree in Computer Science, Computer Engineering, Information Systems, or related STEM fields
Proven track record on producing outstanding research results (Journal and/or Conference publications, and patterns) is a must.
2+ years full lifecycle product development and engineering leadership in highly available, highly scalable, high throughput systems
2+ years of experience in building and delivering sophisticated solutions that leverage various AI solutions, machine learning algorithms or technologies and are able to scale optimally.
Expert in at least one of the following fields:
o Generative AI
o Machine Learning
o Deep Learning
o Reinforcement Learning
o Natural Language Processing
o Optimization
o Probabilistic Inference
o Information Retrieval
o Recommendation Systems
o Bayesian Inference
o Advanced time series forecasting
Hands-on Experience with most of the following open-source solutions:
o Orchestrate: Airflow, Kubeflow Pipelines, ML Run
o Container: Docker, Kubernetes, Mesos + Marathon
o Model Serving: Kubeflow KF Serving, TF Serving, Seldon-Core, MLflow
o Observability: Prometheus, Grafana, Elasticsearch
o Development:
- Programming Language: Python, Java, Scala, Julia
- IDE: Notebooks, PyCharm, VS Studio
- Machine Learning: TensorFlow, Keras, ScikitLearn, H20.ai, XGBoost, MXNet
- Feature Store: Hopsworks, Feast, or other purposed built Feature Store
- Model Format: ONNX, PMML
Ability to convey complex, technical subject matter in a clear and straightforward manner; demonstrated ability to effectively communicate through written and oral presentations with all levels of the organization
Solid project management skills with the ability to juggle multiple priorities simultaneously in a fast-paced environment
Hands-on Experience with GCP and/or AWS is a plus.