Machine learning Engineer

Title: Machine Learning/AI Engineer Location: Remote Summary of the project/initiatives which describes what’s being done: o Build, modernize and maintain the U.S. Bank AI/ML Platform & related frameworks / solutions. o Participate and contribute in architecture & design reviews. o Build/Deploy AI/ML platform in Azure with open-source applications (Argo, Jupyter Hub/Kubeflow) and/or cloud/SaaS solutions (Azure ML, Databricks). o You will design, develop, test, deploy, and maintain distributed & GPU-enabled Machine Learning Pipelines using K8s/AKS based Argo Workflow Orchestration solutions, while collaborating with Data Scientists. o Enable/Support platform to do distributed data processing using Apache Spark and other distributed / scale technologies. o Build ETL pipelines, ingress / egress methodologies in context to AIML use-cases. o Build highly scalable backend REST APIs for metadata management and other misc. business needs. o Deploy Application in Azure Kubernetes Service using GitLab, Jenkins, Docker, Kubectl, Helm and Manifest o Experience in branching, tagging, and maintaining the versions across different environments in GitLab. o Review code developed by other developers and provide feedback to ensure best practices (e.g., design patterns, accuracy, testability, efficiency etc.) o Work with relevant engineering, operations, business lines, and infrastructure groups to ensure effective architectures and designs and communicate findings clearly to technical and non-technical partners. o Perform functional, benchmark & performance testing and tuning to achieve performant AIML workflow(s), interactive notebook user experiences, and pipelines. o Assess, design & optimize the resources capacities for ML based resource (GPU) intensive workloads. o Communicate processes and results of the application with all parties involved in the product team, like engineers, product owner, scrum master and third-party vendors. Top 5-10 responsibilities for this position: o Experience developing AIML platforms & frameworks (including core offerings such as model training, inferencing, distributed/parallel programming), preferably on Kubernetes and native cloud. o Highly skilled with Python or JAVA programming languages o Highly skilled with database languages like SQL & NoSQL o Experience designing, developing, and deploying highly maintainable, extensible, and testable distributed applications using Python and other languages. o Experience developing ETL pipelines and REST APIs in Python using Flask or Django o Experienced with technologies/frameworks including Kubernetes, Helm Charts, Notebooks, Workflow orchestration tools, and CI/CD & monitoring frameworks. Basic Qualifications: • Bachelor’s/master’s degree in computer science or data science • 6 – 8 years of experience in software development and with data structures/algorithms Required Technical Qualifications / Skills: • Experience with AI/ML open-source projects in large datasets using Jupyter, Argo, Spark, Pytorch, TensorFlow • Experience creating Unit and Functional test cases using PyTest, UnitTest • Experience with training and tuning models in Machine Learning • Experience working with Jupyter Hub • Experience with DB management system like PostgreSQL • Experience in searching, monitoring, and analyzing logs using Splunk/Kibana • GraphQL/Swagger implementation knowledge • Strong understanding and experience with Kubernetes for availability and scalability of applications in Azure Kubernetes Service • Experience building CI/CD pipelines using Cloudbees Jenkins, Docker, Artifactory, Kubernetes, Helm Charts and Gitlab • Experience with tools like Jupyter Hub, Kubeflow, MLFlow, TensorFlow, Scikit, Apache Spark, Kafka • Experience with workflow orchestration tools such as Apache Airflow, Argo workflows • Familiarity with Conda, PyPi, and Node.js package builds