Machine learning engineer Work, Jobs in Burnopfield, Dur (with Salaries)

Senior Machine Learning Engineer
Sage —Newcastle upon Tyne
- Hybrid work
- AWS
- Machine learning
- APIs
Operations Team Leader
National Learning Group —Metrocentre
- £28,000 - £32,000 a year
- Full-time
- Microsoft Excel
- Management
- English
- Free parking
Quick apply
Research Assistant/Associate
Newcastle University —Newcastle upon Tyne
- £33,951 - £36,636 a year
- Full-time
- Doctoral degree
- Master's degree
- University
6d
Full Stack Sofware Engineer
CGI —Newcastle upon Tyne
- Full-time
- Azure
- Java
- AWS
Quick apply
Data Scientist
First Quadrant Labs —Newcastle upon Tyne
- £28,298.70 - £88,103.20 a year
- Full-time
- Java
- SQL
- AWS
Quick apply
Finance Assistant
Origin —Newcastle upon Tyne
- £30,000 - £35,000 a year
- Full-time
- Microsoft Excel
- Administrative experience
- Analysis skills
- Work from home
- Sick pay
Quick apply
2d
Embedded Software Engineer
OnlyCat —Cramlington
- £33,000 - £60,000 a year
- Full-time
- AWS
- C++
- Machine learning
- Free parking
Quick apply
7d
Oliver Wyman - Data & Analytics - 6 month Analyst Internship - Newcastle 2026
Oliver Wyman —Newcastle upon Tyne
- Full-time
- Doctoral degree
- English
- Master's degree
DevOps Engineer - Gateshead or Leeds
TEAM RH FITNESS LTD —Gateshead
- £50,000 - £50,001 a year
- Hybrid work
- DevOps
- AWS
- Computer networking
Quick apply
5d
Cloud Infrastructure Engineer - AWS
Giacom —Prudhoe
- £45,000 - £49,000 a year
- DevOps
- AWS
- Scripting
- Annual leave
Quick apply
Information Governance Manager
Somerset Bridge Group —Newcastle upon Tyne
- Full-time
- Hybrid work
- Management
- Presentation skills
- Financial services
- Annual leave
- Referral programme
Quick apply
5d
Research Systems and Information Officer
Durham University —Durham
- £31,236 - £37,694 a year
- Full-time
- Hybrid work
- University
- Communication skills
- Annual leave
- Employee assistance programme
Platform Engineer
CGI —Newcastle upon Tyne
- Full-time
- Azure
- AWS
- Mentoring
Quick apply
AI Automation Apprentice
Sage —Newcastle upon Tyne
- Azure
- Mentoring
- Business
1d
Test Engineer
Public Sector Resourcing —Newcastle upon Tyne
- Full-time
- Java
- AWS
- JavaScript
Digital Marketing & Web Developer
Sleeky Web Design & Print Ltd —Gateshead
- £25,000 - £35,000 a year
- Part-time
- Hybrid work
- Bakery
- JavaScript
- AI
- Free parking
- Flexitime
Quick apply
1d
Service Desk Engineer
Waterstons —Durham
- £28,000 - £32,000 a year
- Weekend availability
- Hybrid work
- Azure
- AWS
- IT
- Employee assistance programme
- Sick pay
IT Infrastructure Engineer
Vertu Motors —Gateshead
- Up to £38,400 a year
- Full-time
- Azure
- AWS
- Employee assistance programme
Quick apply
14d
Research Assistant in App Development
Newcastle University —Newcastle upon Tyne
- £33,951 - £34,610 a year
- Full-time
- Engineering
- University
- Bachelor's degree
12d
Audience Development Assistant (Term Time Only)
Darlington Borough Council —Durham
- £20,001 - £30,000 a year
- Part-time
- Presentation skills
- IT
- AI
8d

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machine learning engineer jobs near burnopfield, dur

Senior Machine Learning Engineer

Sage -
Newcastle upon Tyne

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Job details

Qualifications

Law
AWS
Docker
Machine learning
REST
APIs
Python

Full job description

Job Description

We are looking for a Senior ML Engineer to take technical ownership of our machine learning production environment. You will lead the transition of experimental models into production-grade services that are reliable, scalable, and cost-effective. Your mission is to build the "highway" that allows our data science team to deploy models rapidly while ensuring those models are observable and fiscally responsible. You will own the entire ML lifecycle—from automated training pipelines to real-time inference clusters—and serve as a key software engineering contributor to our AI product stack.

This is a hybrid role – three days per week in our Newcastle office.

Key Responsibilities

In this role your key responsibilities will be:

Lifecycle & Pipeline Architecture: Design and own the automated "Continuous Training" (CT) and deployment pipelines. Architect reusable, modular infrastructure for model training and serving, ensuring the entire lifecycle is versioned and reproducible.

Software Engineering Best Practices: Lead the team in adopting professional engineering standards. This includes owning the strategy for unit/integration testing, peer code reviews, and applying SOLID principles to ML codebases to ensure they remain modular and maintainable.

ML Observability: Establish and own the telemetry framework for the AI stack. Implement proactive monitoring for system health and model-specific metrics, such as data drift, concept drift, and prediction accuracy.

FinOps & Cost Management: Own the strategy for AI cloud spend. Build monitoring and alerting frameworks to track compute costs (training and inference) and implement optimization strategies like auto-scaling and spot-instance usage.

AI Systems Engineering: Act as a lead software engineer to integrate models into the product ecosystem. Develop high-performance, secure APIs and microservices that wrap our ML capabilities for production consumption.

Data & Model Governance: Own the versioning strategy for the "Holy Trinity" of ML: code, data, and model artifacts. Ensure clear documentation and audit trails for all production deployments.

What we're looking for:

Essential skills (entry requirements):

Demonstrating strong software engineering fundamentals, including production‑quality Python, testing, CI/CD practices, and version control

Designing and operating reliable, versioned REST APIs using an API‑first approach

Building, deploying, and operating backend services in cloud environments, with AWS as the primary platform (experience on other major clouds considered transferable)

Using containerisation and modern deployment approaches, including Docker, automated pipelines, and basic observability

Working effectively with real‑world data and production systems in collaboration with product, data, and platform teams

Bringing either hands‑on experience delivering machine‑learning systems in production or a very strong software‑engineering background with clear motivation to grow into ML and MLOps

Desirable skills (strong differentiators):

Using AWS SageMaker for training, deploying, and operating machine‑learning workloads, or demonstrating equivalent experience on similar cloud ML platforms

Exposing machine‑learning models via APIs (e.g. FastAPI‑based inference services) and operating them reliably at scale

Applying MLOps practices, including model and version management, monitoring, and handling model or data drift

Implementing advanced service patterns such as asynchronous processing, event‑driven architectures, or multi‑version services

Serving LLM or GenAI‑based capabilities in production, including model serving, RAG pipelines, and inference controls

Designing reusable, platform‑level services and shared ML patterns rather than one‑off implementations

Managing cloud operational trade‑offs, including cost efficiency, latency, scalability, and reliability

#LI-MD1

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Refine Your Search

machine learning engineer jobs in burnopfield, dur

Senior Machine Learning Engineer

Operations Team Leader

Research Assistant/Associate

Full Stack Sofware Engineer

Data Scientist

Finance Assistant

Embedded Software Engineer

Oliver Wyman - Data & Analytics - 6 month Analyst Internship - Newcastle 2026

DevOps Engineer - Gateshead or Leeds

Cloud Infrastructure Engineer - AWS

Information Governance Manager

Research Systems and Information Officer

Platform Engineer

AI Automation Apprentice

Test Engineer

Digital Marketing & Web Developer

Service Desk Engineer

IT Infrastructure Engineer

Research Assistant in App Development

Audience Development Assistant (Term Time Only)

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