Senior Data Engineer AI & MLOps, AWS, Python - Software

Salt Search; North East; Hybrid; GBP 125,000 - 150,000; Part time

Job summary

A leading recruitment firm seeks a Senior Data Engineer specializing in AI and MLOps for a remote/hybrid role. The candidate will design production-grade ML pipelines and collaborate with data scientists. Competitive day rates from £300 to £500 based on experience. Required: strong AWS and Python skills, with an emphasis on best practices in data engineering.

Qualifications

• Proven experience as a Senior Data Engineer or MLOps Engineer.
• Strong background in data structures and software engineering principles.
• Advanced proficiency in Python for automation and ML workflows.

Responsibilities

• Architect and maintain ML Ops pipelines to automate deployment.
• Collaborate with data scientists to speed up production.
• Design data wrangling workflows using Python.

Skills

AI

MLOps

AWS architecture

Python

Data engineering best practices

Tools

AWS EC2

AWS S3

Docker

Kubernetes

Job description

Overview

Senior Data Engineer (AI & MLOps) - Software - Newcastle/Hybrid or Remote

Day rate: £300 - £500 (Inside IR35)

Duration: 6 months

Start: ASAP

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.

Key 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.
• Mentor junior engineers and contribute to setting technical standards for the team.

Required Qualifications

• Proven experience as a Senior Data Engineer, MLOps Engineer, or similar role.
• Strong background in data structures, algorithms, and software engineering principles.
• Advanced proficiency in Python for data wrangling, pipeline automation, and ML workflows.
• Expertise in AWS services, including databases (RDS, DynamoDB, Redshift) and machine learning/AI (SageMaker, AI/ML frameworks).
• Hands-on experience with ML pipeline orchestration, CI/CD, and deployment automation.
• Deep understanding of ML Ops practices, including monitoring, scaling, and retraining strategies.
• Familiarity with AIOps concepts and tools for operational automation.

Preferred Skills

• Experience with data science and machine learning model development.
• Knowledge of containerization (Docker, Kubernetes, EKS).
• Exposure to infrastructure-as-code (Terraform, CloudFormation).
• Strong problem-solving, communication, and collaboration skills.

Rates depend on experience and client requirements