Simon James IT Ltd
Machine Learning Engineer with Sagemaker
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Machine Learning Engineer with Sagemaker, offering a hybrid contract in Stratford, London, for the finance industry. Key skills include AWS SageMaker, microservices, Python, and ML Ops experience. Contract length and pay rate are unspecified.
🌎 - Country
United Kingdom
💱 - Currency
£ GBP
-
💰 - Day rate
Unknown
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🗓️ - Date
October 9, 2025
🕒 - Duration
Unknown
-
🏝️ - Location
Hybrid
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📄 - Contract
Unknown
-
🔒 - Security
Yes
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📍 - Location detailed
London Area, United Kingdom
-
🧠 - Skills detailed
#SageMaker #Lambda (AWS Lambda) #Microservices #Redshift #Transformers #GIT #DevOps #REST (Representational State Transfer) #ML Ops (Machine Learning Operations) #REST API #FastAPI #Jupyter #AI (Artificial Intelligence) #Data Science #Python #Security #AWS Machine Learning #SQL (Structured Query Language) #AWS SageMaker #"ETL (Extract #Transform #Load)" #Hugging Face #AWS (Amazon Web Services) #ML (Machine Learning) #Flask #R #Version Control
Role description
ML Ops Engineer (Data Science - AWS Sagemaker)
Stratford, London (Hybrid – 2-3 days)
Are you passionate about bridging the gap between Data Science and DevOps? We're looking for an experienced ML Ops Engineer with a data science background to help scale AI/ML solutions into production using cutting-edge AWS technologies. The contract is working for a regulatory Body in the Finance industry
What You’ll Do
• Deploy and maintain ML models using AWS SageMaker (ideally some Bedrock & Glue)
• Build microservices and APIs to serve models (e.g., Hugging Face Transformers)
• Automate workflows and manage full ML lifecycle
• Collaborate with cross-functional teams and mentor data scientists
• Drive CI/CD integration and DevOps best practices
What You’ll Bring
• Experience deploying and maintaining AI/ML models in production environment using AWS SageMaker (Ideally with AWS Fargate, Lambda, Redshift, etc.)
• Hands-on experience with AWS Machine Learning and Data services: SageMaker
• Develop and host microservices and REST APIs using Flask, FastAPI
• SQL, version control (Git), and working with Jupyter or RStudio environments.
• Strong Python (or R) skills and hands-on ML experience
• Excellent communication and stakeholder engagement skills
Why Join Us?
• Work on impactful AI/ML projects
• Be part of a collaborative, product-first team
• Grow your skills in a dynamic, tech-forward environment
Security: SC Clearance preferred or but will consider SC eligible
ML Ops Engineer (Data Science - AWS Sagemaker)
Stratford, London (Hybrid – 2-3 days)
Are you passionate about bridging the gap between Data Science and DevOps? We're looking for an experienced ML Ops Engineer with a data science background to help scale AI/ML solutions into production using cutting-edge AWS technologies. The contract is working for a regulatory Body in the Finance industry
What You’ll Do
• Deploy and maintain ML models using AWS SageMaker (ideally some Bedrock & Glue)
• Build microservices and APIs to serve models (e.g., Hugging Face Transformers)
• Automate workflows and manage full ML lifecycle
• Collaborate with cross-functional teams and mentor data scientists
• Drive CI/CD integration and DevOps best practices
What You’ll Bring
• Experience deploying and maintaining AI/ML models in production environment using AWS SageMaker (Ideally with AWS Fargate, Lambda, Redshift, etc.)
• Hands-on experience with AWS Machine Learning and Data services: SageMaker
• Develop and host microservices and REST APIs using Flask, FastAPI
• SQL, version control (Git), and working with Jupyter or RStudio environments.
• Strong Python (or R) skills and hands-on ML experience
• Excellent communication and stakeholder engagement skills
Why Join Us?
• Work on impactful AI/ML projects
• Be part of a collaborative, product-first team
• Grow your skills in a dynamic, tech-forward environment
Security: SC Clearance preferred or but will consider SC eligible
