Recruiter: Daniel McCarthy
Career Grade: D
Internal Closing Date: 16/2/26
Why this job matters
We are looking for an AWS MLOps Engineering Specialist to deploy and operate production grade machine learning platforms using the AWS SageMaker MLOps framework. This role focuses on enabling the full ML lifecycle—data preparation, model deployment, monitoring, and retraining—through standardised, automated, and governed pipelines. You will work at the intersection of data science, cloud engineering, and DevOps, ensuring models built in SageMaker can be reliably deployed at scale, monitored for drift and performance, and governed in line with enterprise and regulatory expectations. You will play a key role in standardising ML lifecycle practices, automating pipelines, and embedding operational excellence, security, and cost efficiency into AI/ML workloads.
What you’ll be doing
1. Design and implement end to end MLOps workflows using AWS SageMaker, including:
• SageMaker Pipelines for training and orchestration
• SageMaker Feature Store for feature management
• SageMaker Model Registry for model versioning and approvals
• SageMaker Experiments for lineage and metadata tracking
2. Enable consistent promotion of models across environments (dev / test / pre-prod / prod)
3. Implement automated retraining strategies triggered by data or performance changes
4. Implement and mature an MLOps framework covering code/data/model versioning, automated testing, release governance, rollback strategies and environment promotion controls.
5. Apply security by design across SageMaker workloads by adopting IAM least privilege roles for training, pipelines and endpoints and ensuring Network isolation using VPC attached SageMaker resources.
6. Implement model monitoring (e.g. data quality, model quality, bias drift, feature attribution drift) and alerting driving automated responses such as retraining triggers and controlled redeployments.
7. Put in place drift detection, evaluation routines, and model performance reporting; partner with data science to define thresholds, baselines and acceptance criteria.
7. Define standards for documentation, change management and quality gates that reduce MTTR and improve platform reliability.
8. Partner with data scientists to productionise notebooks and experiments into managed pipelines.
9. Build scalable inference solutions using SageMaker real time and serverless endpoints.
Experience Required
* Degree in Computer Science/Engineering (or equivalent practical experience leading production cloud/ML platforms).
* AWS certifications strongly preferred (at least one of these) :
1. DevOps Engineer Professional
2. Machine Learning Engineer – Associate
3. AI Practitioner for GenAI fundamentals
* Knowledge of data governance, lineage, and model explainability practices
* Strong hands-on experience with MLOps practices: CI/CD, versioning (code/data/model), release governance, and production monitoring.
* Strong AWS experience, particularly with Amazon SageMaker for ML deployment and monitoring including drift/quality monitoring approaches.
* Experience designing observability for serverless systems (logs/metrics/traces) and implementing distributed tracing and dashboards using open standards and AWS tooling.
The skills you’ll need
Data Modelling
DevOps
APIs/Web Service Integration
Programming/Scripting
Data Privacy
Big Data Processing
Cloud Computing
Artificial Intelligence/Machine Learning
Performance Monitoring
Data Analysis
Data Management
Artificial Intelligence (AI) Ethics
Algorithm Design
Data Model Management
Machine Learning Operations (MLOps)
Decision Making
Growth Mindset
Inclusive Leadership
DataOps
Our leadership standards
Looking in:
Leading inclusively and Safely
I inspire and build trust through self-awareness, honesty and integrity.
Owning outcomes
I take the right decisions that benefit the broader organisation.
Looking out:
Delivering for the customer
I execute brilliantly on clear priorities that add value to our customers and the wider business.
Commercially savvy
I demonstrate strong commercial focus, bringing an external perspective to decision-making.
Looking to the future:
Growth mindset
I experiment and identify opportunities for growth for both myself and the organisation.
Building for the future
I build diverse future-ready teams where all individuals can be at their best.
About us
BT Group was the world’s first telco and our heritage in the sector is unrivalled. As home to several of the UK’s most recognised and cherished brands – BT, EE, Openreach and Plusnet, we have always played a critical role in creating the future, and we have reached an inflection point in the transformation of our business.
Over the next two years, we will complete the UK’s largest and most successful digital infrastructure project – connecting more than 25 million premises to full fibre broadband. Together with our heavy investment in 5G, we play a central role in revolutionising how people connect with each other.
While we are through the most capital-intensive phase of our fibre investment, meaning we can reward our shareholders for their commitment and patience, we are absolutely focused on how we organise ourselves in the best way to serve our customers in the years to come. This includes radical simplification of systems, structures, and processes on a huge scale. Together with our application of AI and technology, we are on a path to creating the UK’s best telco, reimagining the customer experience and relationship with one of this country’s biggest infrastructure companies.
Change on the scale we will all experience in the coming years is unprecedented. BT Group is committed to being the driving force behind improving connectivity for millions and there has never been a more exciting time to join a company and leadership team with the skills, experience, creativity, and passion to take this company into a new era.
A FEW POINTS TO NOTE:
Although these roles are listed as full-time, if you’re a job share partnership, work reduced hours, or any other way of working flexibly, please still get in touch.
We will also offer reasonable adjustments for the selection process if required, so please do not hesitate to inform us.
DON'T MEET EVERY SINGLE REQUIREMENT?
Studies have shown that women and people who are disabled, LGBTQ+, neurodiverse or from ethnic minority backgrounds are less likely to apply for jobs unless they meet every single qualification and criteria. We're committed to building a diverse, inclusive, and authentic workplace where everyone can be their best, so if you're excited about this role but your past experience doesn't align perfectly with every requirement on the Job Description, please apply anyway - you may just be the right candidate for this or other roles in our wider team.