Senior Data Engineer (AWS SageMaker, ML) Contract

Overview

My new client is looking for a Senior Data Engineer with expertise in AI, MLOps, and AWS architecture to design and deliver production-grade machine learning pipelines. The ideal candidate will be passionate about bridging the gap between data science experimentation and scalable production systems, driving automation, and enabling faster innovation cycles.

Responsibilities

• Architect, build, and maintain production-grade ML Ops pipelines to automate deployment, monitoring, and scaling of machine learning models.
• Collaborate with data scientists and ML engineers to reduce time-to-production for experiments and prototypes.
• Design and optimize data wrangling and transformation workflows using Python.
• Leverage AWS cloud services (EC2, S3, Lambda, SageMaker, RDS, DynamoDB, Redshift, etc.) to build robust, scalable, and cost-effective solutions.
• Apply AIOps practices to enhance monitoring, automation, and resilience of ML systems.
• Implement best practices in data engineering, version control, CI / CD, and infrastructure as code.
• Ensure the security, reliability, and compliance of data pipelines and deployed ML solutions.

Required Qualifications

Preferred Skills

Role details

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