ML Platform Engineer

Our Company

Changing the world through digital experiences is what Adobes all about. We give everyonefrom emerging artists to global brandseverything they need to design and deliver exceptional digital experiences! Were passionate about empowering people to create beautiful and powerful images videos and apps and transform how companies interact with customers across every screen.

Were on a mission to hire the very best and are committed to creating exceptional employee experiences where everyone is respected and has access to equal opportunity. We realize that new ideas can come from everywhere in the organization and we know the next big idea could be yours!

The Challenge

We are looking for a highly motivated individuals knowledgeable in ML Ops/ Platform engineering to be part of our Advertising Cloud Search Social Commerce a leading digital marketing spend optimization platform helping enterprise clients achieving their marketing goals. We are now faced with exciting challenge of continuing the legacy and at the same time evolving and owning the digital marketing space through our innovative solutions. Its a robust agile team that collaborates and works across all functions of true product development. You must be that individual who is highly engaged motivated and excels at critical thinking and problem solving!

What youll do

• Model Lifecycle Management: Manage model versioning deployment strategies rollback mechanisms and A/B testing frameworks. Coordinate model registries artifacts and promotion workflows in collaboration with ML Engineers Develop CI/CD and orchestration workflows using GitLab CI GitHub Actions CircleCI Airflow Argo Workflows or similar tools.
• Review and optimize data science models including code refactoring containerization deployment versioning and performance tuning. Implement model testing validation and automated QA pipelines ensuring reproducibility and compliance.
• Monitor models in production including data drift concept drift performance degradation and system reliability.
• Collaborate multi-functionally with data scientists data engineers and architects; build documentation and improve team processes.
• Ensure governance security and compliance for ML pipelines (access controls audit logs model reproducibility lineage).

What you need to succeed

• Bachelors degree or advanced degree or equivalent experience in Computer Science Software Engineering or a related technical field.
• Strong ability to design and implement cloud architectures for end-to-end ML workflows on AWS.
• Hands-on experience with MLOps frameworks like MLflow Kubeflow Airflow or similar.
• Proficiency with Docker Kubernetes (EKS/GKE/AKS) and enterprise platforms like OpenShift.
• Strong programming skills in Python; familiarity with Go Ruby or Bash scripting. Experience with common ML libraries such as scikit-learn TensorFlow Keras PyTorch.
• Experience with software engineering guidelines including version control testing and automation.
• Ability to understand data science workflows experiment tracking and feature engineering tools.
• Strong communication skills; ability to work collaboratively in multi-functional teams.
• Knowledge of cloud services such as AWS Sagemaker Azure ML GCP Vertex AI.
• Exposure to feature stores like Feast Tecton or Databricks Feature Store.
• Experience with observability tools (Prometheus Grafana ELK CloudWatch Datadog).
• Experience implementing model governance & lineage with tools like MLflow Registry SageMaker Model Registry or Vertex ML Metadata.
• Familiarity with infrastructure-as-code (Terraform CloudFormation).

Adobe is proud to be anEqual Employment Opportunityemployer. We do not discriminate based on gender race or color ethnicity or national origin age disability religion sexual orientation gender identity or expression veteran status or any other applicable characteristics protected by law.Learn more.

Adobe aims to make accessible to any and all users. If you have a disability or special need that requires accommodation to navigate our website or complete the application process emailor call .