Description

You will lead the architectural design and technical implementation of scalable software and machine learning systems.

Responsibilities

• Build and manage MLOps pipelines using AWS SageMaker.
• Implement CI/CD workflows using Jenkins, Bitbucket, Kubernetes, and OpenShift.
• Integrate SOA, ESB, JMS messaging, and Web Services technologies.
• Support data science workflows through software development and test automation.
• Drive delivery using Agile methodologies including Scrum, Lean, XP, and Kanban.

Required Skills

• 8+ years of experience in programming, engineering, or systems analysis.
• 7 years of experience in software engineering.
• Hands-on experience with AWS cloud services.
• Proficiency in Python.
• 4+ years experience deploying and administering J2EE application servers and containers such as Websphere, JBoss, or Tomcat.
• 4+ years experience with SOA, ESB, JMS messaging, transaction, XML, and Web Services integration.
• Experience with Kubernetes and Bitbucket.
• Knowledge of XML.
• B.S. in Computer Science, Information Systems, or equivalent experience.

Preferred Skills

• In-depth knowledge of machine learning frameworks like TensorFlow, Keras, or PyTorch.
• AWS Machine Learning, DevOps Engineer, SysOps Administrator, or Advanced Networking certifications.
• Experience in financial services or other highly regulated industries.

Key Skills

Education

Any Gradute