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ML Engineer (with Data Science Background)
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an ML Engineer (with Data Science Background) for a 6-month contract in London, requiring expertise in AWS SageMaker, ML Ops, DevOps, and microservices. Strong collaboration and communication skills are essential.
🌎 - Country
United Kingdom
💱 - Currency
£ GBP
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💰 - Day rate
Unknown
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🗓️ - Date
October 2, 2025
🕒 - Duration
More than 6 months
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🏝️ - Location
On-site
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📄 - Contract
Fixed Term
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🔒 - Security
Unknown
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📍 - Location detailed
London Area, United Kingdom
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🧠 - Skills detailed
#AWS Machine Learning #DevOps #SQL (Structured Query Language) #AWS SageMaker #FastAPI #AWS (Amazon Web Services) #Version Control #Data Science #REST API #REST (Representational State Transfer) #Jupyter #AI (Artificial Intelligence) #Model Deployment #Microservices #ML (Machine Learning) #SageMaker #Flask #ML Ops (Machine Learning Operations) #Deployment #GIT
Role description
ML Ops Engineer (with Data Science and DevOps experience) 3 days a week London - 6 months
Key requirement:
• ML Ops Engineer with experience in data science, DevOps, and AWS SageMaker for model deployment (ML lifecycle).
• Excellent soft skills
Essential skills:
Demonstrated experience deploying and maintaining AI/ML models in production environment using AWS SageMaker.
Hands-on experience with AWS Machine Learning and Data services: SageMaker
Ability to develop and host microservices and REST APIs using Flask, FastAPI, or equivalent frameworks.
Proficiency with SQL, version control (Git), and working with Jupyter or RStudio environments.
Strong cross-functional collaboration skills and the ability to explain technical concepts to nontechnical stakeholders.
URGENT CONTRACT
ML Ops Engineer (with Data Science and DevOps experience) 3 days a week London - 6 months
Key requirement:
• ML Ops Engineer with experience in data science, DevOps, and AWS SageMaker for model deployment (ML lifecycle).
• Excellent soft skills
Essential skills:
Demonstrated experience deploying and maintaining AI/ML models in production environment using AWS SageMaker.
Hands-on experience with AWS Machine Learning and Data services: SageMaker
Ability to develop and host microservices and REST APIs using Flask, FastAPI, or equivalent frameworks.
Proficiency with SQL, version control (Git), and working with Jupyter or RStudio environments.
Strong cross-functional collaboration skills and the ability to explain technical concepts to nontechnical stakeholders.
URGENT CONTRACT
