Python Work, Jobs in Wideopen, Nbl (with Salaries)

Senior Machine Learning Engineer
Sage —Newcastle upon Tyne
- Hybrid work
- AWS
- Machine learning
- APIs
Data Scientist - Credit Eligibility
M-KOPA —Newcastle upon Tyne
- Full-time
- Remote
- SQL
- Financial services
- Communication skills
Software Engineer – Engineering Applications
Vulcain Engineering Group —Hexham
- Hybrid work
- Azure
- Engineering
- English
- Employee assistance programme
- Referral programme
Technical UI Designer - 12 Month Contract
Keywords Studios —Gateshead
- Hybrid work
- C++
- JavaScript
- Python
- Free parking
- Flexible schedule
Quick apply
Senior Associate, Payroll Integration, Newcastle Upon Tyne/Manchester/Belfast
EY —Newcastle upon Tyne
- Microsoft Powerpoint
- Microsoft Word
- Microsoft Excel
2d
Test Engineer (SC Cleared)
Scrumconnect Consulting —Newcastle upon Tyne
- £50,000 - £55,000 a year
- Java
- SQL
- AWS
Senior Software Engineer
OpenWorks Engineering —Prudhoe
- Full-time
- Computer Science
- DevOps
- Engineering
Quick apply
2d
Oliver Wyman - Data & Analytics Research Fellowship - Newcastle upon Tyne
Oliver Wyman —Newcastle upon Tyne
- Full-time
- Doctoral degree
- English
- Machine learning
Full Stack Developer
Version 1 —Newcastle upon Tyne
- Full-time
- AWS
- APIs
- Agile
- Employee assistance programme
- Employee discount
Quick apply
Senior Database Engineer (UK Remote)
Turnitin, LLC —Newcastle upon Tyne
- Full-time
- Remote
- AWS
- Scripting
- Linux
- Annual leave
Quick apply
Senior AI Product & Research Engineer (Consultant)
Version 1 —Newcastle upon Tyne
- Full-time
- AWS
- AI
- Python
- Employee assistance programme
- Employee discount
Quick apply
10d
DevOps Engineer - Newcastle
Accenture —Newcastle upon Tyne
- Full-time
- AWS
- Scripting
- APIs
AWS Devops Engineer (SC Cleared)
Scrumconnect Consulting —Newcastle upon Tyne
- £50,000 - £60,000 a year
- DevOps
- SQL
- AWS
Embedded Design Engineer - FPGA Academy
Leonardo UK Ltd —Newcastle upon Tyne
- £37,400 - £71,400 a year
- Full-time
- Hybrid work
- Doctoral degree
- Engineering
- Master's degree
- Flexible schedule
- Referral programme
DevOps Engineer
Everflow —Peterlee
- £39,400 - £63,000 a year
- Full-time
- Azure
- Scripting
- Linux
Test Automation Engineer
Version 1 —Newcastle upon Tyne
- Full-time
- Java
- AWS
- JavaScript
- Employee assistance programme
- Employee discount
Quick apply
11d
Staff Software Engineer
Lunar —Newcastle upon Tyne
- Full-time
- JavaScript
- In-person
- Communication skills
DevOps Engineer
hireful —Durham
- £50,000 - £63,000 a year
- Full-time
- Hybrid work
- Azure
- Scripting
- Python
Quick apply
Senior Portfolio Analyst
LeoVegas UK —Newcastle upon Tyne
- Full-time
- Hybrid work
- English
- SQL
- Mentoring
- Free parking
- Annual leave
Senior DevOps Engineer - Newcastle
Accenture —Newcastle upon Tyne
- Full-time
- DevOps
- AWS
- Scripting

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python jobs near wideopen, nbl

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

python jobs in wideopen, nbl

Senior Machine Learning Engineer

Data Scientist - Credit Eligibility

Software Engineer – Engineering Applications

Technical UI Designer - 12 Month Contract

Senior Associate, Payroll Integration, Newcastle Upon Tyne/Manchester/Belfast

Test Engineer (SC Cleared)

Senior Software Engineer

Oliver Wyman - Data & Analytics Research Fellowship - Newcastle upon Tyne

Full Stack Developer

Senior Database Engineer (UK Remote)

Senior AI Product & Research Engineer (Consultant)

DevOps Engineer - Newcastle

AWS Devops Engineer (SC Cleared)

Embedded Design Engineer - FPGA Academy

DevOps Engineer

Test Automation Engineer

Staff Software Engineer

DevOps Engineer

Senior Portfolio Analyst

Senior DevOps Engineer - Newcastle

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