Cloud MLOps Engineer supporting Data Science and Engineering teams by automating CI/CD pipelines and managing multi - cloud infrastructure for ML production.
About the role
- Lead advanced machine learning model development and optimization at PayPal. Collaborate with teams to deploy scalable ML solutions in production environments.
Responsibilities
- Lead the development and optimization of advanced machine learning models.
- Oversee the preprocessing and analysis of large datasets.
- Deploy and maintain ML solutions in production environments.
- Collaborate with cross-functional teams to integrate ML models into products and services.
- Monitor and evaluate the performance of deployed models, making necessary adjustments.
Requirements
- 5+ years relevant experience and a Bachelor’s degree OR Any equivalent combination of education and experience
- Extensive experience with ML frameworks like TensorFlow, PyTorch, or scikit-learn
- Expertise in cloud platforms (AWS, Azure, GCP) and tools for data processing and model deployment
- Experience owning end-to-end ML model lifecycles, including training, evaluation, deployment, monitoring, and retraining in production environments
- Strong hands-on experience with MLOps best practices and platforms, such as experiment tracking, model versioning, and automated training/deployment pipelines (e.g., MLflow, Kubeflow, Airflow, SageMaker, Vertex AI)
- Experience building and scaling LLM- and GenAI-based systems, including fine-tuning, inference optimisation, prompt management, and retrieval-augmented generation (RAG) pipelines
- Proven ability to design scalable, reliable, and cost-efficient ML inference systems, with familiarity in containerisation, orchestration, and infrastructure-as-code (Docker, Kubernetes, Terraform)
- Experience with large-scale data processing and distributed systems (e.g., Spark) and integrating ML solutions into complex production architectures
- Understanding of Responsible AI practices (explainability, fairness, robustness, compliance) and demonstrated technical leadership or mentorship influencing ML architecture and standards.
Benefits
- generous paid time off
- healthcare coverage for you and your family
- resources to create financial security and support your mental health
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
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