Principal Machine Learning Engineer

Entain is hiring a Principal Machine Learning Engineer to join our wider Enterprise DS&AI team that supports our core Brands and Regions.

As a Principal Machine Learning Engineer you will support design develop deploy and maintain advanced software and infrastructure capabilities within the specialised technical domain of Machine Learning Engineering MLOps AIOps and GenAI enablement.

Reporting to the ML Engineering Manager you will be part of the Enterprise DS&AI Centre of Excellence focused on creating scaling and enhancing machine learning platforms frameworks and operational capabilities of significant complexity.

You will play a key role in helping Data Science and AI teams move faster operate more reliably and deliver production-grade ML and AI solutions across the business.

Are you ready to be part of our journey delivering technical excellence and collaborating with one of the worlds biggest online gaming and entertainment groups

What you will do

As a Principal ML Engineer you will:

• Lead the design and implementation of scalable MLOps and AIOps frameworks that simplify how Data Science teams develop train deploy monitor and maintain machine learning models.
• Design build and maintain reusable ML infrastructure components using AWS services Snowflake Prefect CI/CD pipelines and other enterprise-grade tools.
• Provide technical leadership across ML engineering initiatives ensuring solutions are robust secure scalable observable and aligned with engineering best practices.
• Support the development of ML platform capabilities covering experimentation model training orchestration deployment monitoring retraining incident management and governance.
• Collaborate closely with Data Scientists ML Engineers Data Engineers Cloud Engineers Product Owners and business stakeholders to understand requirements and translate them into practical technical solutions.
• Contribute to the design and implementation of GenAI and LLM-based solutions including enterprise AI assistants agentic workflows AI automation and secure access to foundation models.
• Build frameworks templates standards and reference implementations that reduce duplicated effort and accelerate delivery across multiple Data Science teams.
• Drive the adoption of modern software engineering practices including automated testing infrastructure as code containerisation CI/CD IaC model versioning and production monitoring.
• Support orchestration and automation of ML workloads using tools such as Prefect AWS-native services and event-driven patterns.
• Help define architectural standards and technical roadmaps for ML infrastructure MLOps AIOps and GenAI capabilities.
• Review technical designs and code mentor other engineers and promote high engineering standards across the team.
• Identify operational risks technical debt and platform limitations and propose pragmatic improvements.

Qualifications :

What we are looking for

We are looking for an experienced technical leader with strong hands-on engineering capability and a deep understanding of how to bring machine learning systems into production.

You should have:

• Strong experience as a Machine Learning Engineer MLOps Engineer AI Platform Engineer Cloud ML Engineer or similar role.
• Proven experience designing and operating production-grade ML infrastructure and MLOps platforms.
• Strong hands-on experience with Cloud providers (AWS) especially services related to machine learning orchestration compute storage networking security and deployment.
• Experience with Snowflake as a data platform including data access patterns integration with ML workflows and performance-aware data consumption.
• Experience with workflow orchestration tools such as Prefect Airflow Dagster or similar.
• Strong experience implementing IaC and CI/CD pipelines for software data and machine learning workflows.
• Strong Python engineering skills and experience building maintainable tested production-ready code.
• Experience with containerisation using Docker and ideally deployment on ECS EKS Kubernetes or equivalent platforms.
• Good understanding of model training batch inference real-time inference model monitoring retraining and ML lifecycle management.
• Experience working with stakeholders to gather requirements shape technical solutions and coordinate delivery across multiple teams.
• Exposure to GenAI LLMs AI agents RAG architectures prompt orchestration or enterprise AI assistant implementations.
• Ability to define technical standards influence architecture mentor engineers and guide teams through complex technical decisions.

Nice to have

Experience with any of the following would be beneficial:

• AWS SageMaker Bedrock Lambda ECS EKS Step Functions EventBridge CloudWatch IAM S3 ECR or related services.
• MLflow model registries feature stores model observability drift detection and automated retraining patterns.
• AIOps use cases such as anomaly detection incident enrichment automated ticket creation event correlation alert deduplication or operational intelligence.
• Building internal developer platforms reusable frameworks project templates or self-service capabilities for technical teams.
• Secure GenAI patterns including guardrails access control PII protection auditability and model governance.
• Experience in regulated high-scale or customer-facing digital environments.
• Knowledge of online gaming entertainment betting or high-volume transactional platforms.

Key behaviors and capabilities

You will be successful in this role if you are:

• Technically strong and comfortable operating at both architectural and implementation levels.
• Pragmatic delivery-focused and able to balance ideal engineering practices with business priorities.
• Able to simplify complex technical concepts for different audiences.
• Comfortable influencing without always having direct authority.
• Proactive in identifying risks gaps and opportunities for improvement.
• Passionate about creating reusable frameworks and reducing operational friction for other teams.
• A strong collaborator who can work across Data Science Engineering Cloud Security Product and business functions.
• Committed to engineering excellence automation reliability and continuous improvement.

Additional Information :

At Entain we know that signing top players requires a great starting package and plenty of support to inspire peak performance. Join us and a competitive salary is just the beginning. Working for us in our London or Gibraltar offices you can expect to receive great benefits like:

• Competitive salaries
• Option to buy/ sell and carry over annual leave
• Additional days leave to take on Christmas eve or NYE
• Option to buy and sell and move over annual leave
• Relocation support depending on existing location
• Private Healthcare
• Hybrid working
• Room to grow and develop throughout the business!

And outside of this youll have the chance to turn recognition from leaders and colleagues into amazing prizes. Join a winning team of talented people and be a part of an inclusive and supporting community where everyone is celebrated for being themselves. 

Should you need any adjustments or accommodations to the recruitment process at either application or interview please contact us.

Remote Work :

No

Employment Type :

Full-time