JPMorgan Software Engineer III - Infra 

United Kingdom, England, London 

693564789

Responsibilities

• Collaborate with data scientists and research/machine learning engineers to deliver products to production.
• Build and maintain scalable infrastructure as code in the cloud (private & public).
• Manage infrastructure for model training/serving and governance.
• Manage data infrastructure supporting the inference pipelines.
• Contribute significantly to architecture and software management discussions & tasks
• Rapid prototyping & shorten development cycles for our software and AI/ML products:
  • Build infrastructure for our AI/ML data pipelines & workstreams from data analysis, experimentation, model training, model evaluation, deployment, operationalization, and tuning to visualization.
  • Improve and maintain our automated CI/CD pipeline while collaborating with our stakeholders, various testing partners and model contributors.
• Increase our deployment velocity, including the process for deploying models and data pipelines into production.

Requirements

• Minimum Bachelor of Science degree in Computer Science, Software Engineering, Electrical Engineering, Computer Engineering or related field.
• Experience in containerization - Docker/Kubernetes.
• 3+ years of experience in AWS cloud and services (S3, Lambda, Aurora, ECS, EKS, SageMaker, Bedrock, Athena, Secrets Manager, Certificate Manager etc.)
• Proven DevOps/MLOps experience provisioning and maintaining infrastructure leveraging some of the following: Terraform, Ansible, AWS CDK, CloudFormation.
• Experience with CI/CD pipelines ex. Jenkins/Spinnaker.
• Experience with monitoring tools such as Prometheus, Grafana, Splunk and Datadog.
• Proven programming/scripting skills with some of the modern programming languages like Python.
• Solid software design, problem solving and debugging skills.
• Strong interpersonal skills; able to work independently as well as in a team.

Desirable

• You have a strong commitment to development best practices and code reviews.
• You believe in continuous learning, sharing best practices, encouraging and elevating less experienced colleagues as they learn.
• Experience with data labelling, validation, provenance and versioning.