Machine Learning Engineer

Job description

Description

CONTRACTOR MUST BE ELIGIBLE FOR BPSS

Role Title: MLOps Engineer

Location: Glasgow

Duration: 31/12/2026

Days on site: 2-3

Rate: 328 £/day via umbrella

Role Overview

We are seeking a highly skilled MLOps Engineer with strong expertise in AWS-native services, infrastructure automation, and end to end ML workflow operations. The ideal candidate will have deep experience with CloudFormation, SageMaker, Glue, Lambda, Spark, and Python, along with solid understanding of machine learning concepts, data pipelines, model monitoring, and production deployment.

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Key Responsibilities

• Design, automate, and maintain scalable ML infrastructure using AWS CloudFormation and AWS-native services.

• Build, deploy, and manage ML models on Amazon SageMaker (training, tuning, hosting, endpoints, pipelines).

• Develop and optimize distributed data processing workflows using Apache Spark, AWS Glue, and related ETL frameworks.

• Build serverless automation and integration logic using AWS Lambda and Python-based microservices.

• Implement MLOps best practices across the ML lifecycle—data preprocessing, feature engineering, model training, testing, deployment, and monitoring.

• Create reproducible and automated model CI/CD pipelines integrating data, code, and infrastructure components.

• Establish continuous model monitoring frameworks (data drift, concept drift, performance degradation).

• Ensure secure, scalable, and compliant ML workloads aligned with enterprise standards (IAM, KMS, networking, observability).

• Partner with data scientists, data engineers, and cloud architects to operationalize ML solutions in production.

• Troubleshoot ML pipelines, model deployment issues, and infrastructure bottlenecks.

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Required Skills & Experience

• 4–7 years of hands on experience in MLOps, ML engineering, or cloud-based automation roles.

• Strong expertise in AWS CloudFormation for IaC automation (must have).

• Solid experience with Amazon SageMaker (training, inference, pipelines, model registry).

• Strong hands on experience with AWS Glue and Apache Spark for ETL and distributed data processing.

• Proficiency in Python, particularly for ML/ETL automation and production pipelines.

• Strong understanding of:

o ML lifecycle management

o Data preprocessing & feature engineering

o Model evaluation, versioning, and deployment strategies

o Model performance monitoring & alerting

• Experience with CI/CD pipelines for ML (CodePipeline, GitHub Actions, Jenkins, or similar).

• Good understanding of ML frameworks (TensorFlow, PyTorch, Scikit-learn) for integration and packaging.

• Strong knowledge of AWS services relevant to ML and automation (Lambda, S3, Step Functions, IAM, KMS, CloudWatch).

Extra information

Status

Open

Education Level

Secondary School

Location

Glasgow City

Type of Contract

Full-time jobs

Published at

04-02-2026

Full UK/EU driving license preferred

No

Car Preferred

No

Must be eligible to work in the EU

No

Cover Letter Required

No

Languages

English