Location: Remote
Contract Duration: 2–3 Months
Compensation: USD 5,000–5,500 Gross / Month
Start Date: Immediate / As soon as possible
English C1
Are you available to work with at least 4 hours of overlap with the PST timezone?

About the Role:

We are looking for a skilled Senior MLOps Engineer with 6+ years of experience to join our team for a short-term assignment. The role requires strong hands-on expertise in AWS SageMaker, MLflow, and ML infrastructure. The ideal candidate will support the design and deployment of scalable and automated ML workflows over a 2–3 month period.

Key Responsibilities:

• Develop and manage ML pipelines using SageMaker and MLflow

• Implement CI/CD practices for ML model lifecycle (training, validation, deployment)

• Deploy and monitor models in production environments

• Improve existing ML infrastructure for reliability and scalability

• Work closely with data scientists and platform engineers to integrate workflows

• Document processes and ensure effective knowledge transfer

Requirements:

• 6+ years of experience in MLOps or ML infrastructure roles

• Strong expertise with AWS SageMaker (pipelines, model registry, deployment endpoints)

• Proficient in MLflow for model tracking and deployment

• Experience with cloud environments (preferably AWS), Docker, and optionally Kubernetes

• Familiarity with CI/CD tools like GitHub Actions, Jenkins, or AWS CodePipeline

• Strong communication and documentation skills

• Ability to work independently and deliver in a short timeframe