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Senior Machine Learning Engineer

This role is for a Senior Machine Learning Engineer in Bristol, UK, on a 6-month contract at £500 - £530 per day. Requires strong AWS, Python, and MLOps skills, with experience in deploying ML models to edge systems and cloud environments.
🌎 - Country
United Kingdom
💱 - Currency
£ GBP
💰 - Day rate
Unknown
Unknown
530
🗓️ - Date discovered
February 22, 2025
🕒 - Project duration
Unknown
🏝️ - Location type
On-site
📄 - Contract type
Outside IR35
🔒 - Security clearance
Yes
📍 - Location detailed
City Of Bristol, England, United Kingdom
🧠 - Skills detailed
#Python #Hugging Face #Redis #Grafana #Consul #ML (Machine Learning) #Databases #PyTorch #SQL (Structured Query Language) #Deployment #AWS (Amazon Web Services) #Cloud
Role description
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Machine Learning Lead

Industry: Technology

Location: Bristol, NA, United Kingdom

Salary: £500 - £530 per day

Contract Type: Contract

IR35 Status: Outside IR35

On-Site Requirement: 3 days in Bristol

Job Description

We are currently working with a consultancy looking for a Machine Learning Technical Lead to join an experienced team developing cutting-edge machine learning solutions. This is a contract role with a focus on deploying ML models to edge systems and leveraging cloud solutions for training and production implementations.

Key Responsibilities:
• Lead machine learning initiatives with a strong focus on production deployment.
• Develop and optimise ML models for edge computing and cloud-based training.
• Experience with AWS.
• Implement and maintain MLOps pipelines, particularly using ClearML.
• Monitor models and infrastructure using tools such as Grafana.
• Work with Redis and SQL databases in a cloud environment.
• Source models from platforms such as Hugging Face and work with technologies like Nvidia Edge Compute, Llamas, and Omniverse.
• Ensure all ML models and codes are well-documented and explainable.

Requirements:
• Proven experience as a Machine Learning Lead.
• Strong expertise in AWS.
• Experience in deploying ML models to edge systems and cloud-based training.
• Proficiency in Python and frameworks such as PyTorch.
• Strong knowledge of LLMs (Large Language Models) and ML modelling.
• MLOps experience, particularly with ClearML.
• Ability to monitor ML pipelines with tools such as Grafana.
• Experience working with Redis and SQL databases.
• Ability to explain, document, and optimise ML code for production environments.
• Experience working on production builds, MVPs, and proof of concepts.
• SC Clearance or the ability to obtain it.