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.
- 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.
- Strong experience as a Machine Learning Engineer, MLOps Engineer, AI Platform Engineer, Cloud ML Engineer, or similar role. (required)
- Proven experience designing and operating production-grade ML infrastructure and MLOps platforms. (required)
- Strong hands-on experience with Cloud providers (AWS), especially services related to machine learning, orchestration, compute, storage, networking, security, and deployment. (required)
- Experience with Snowflake as a data platform, including data access patterns, integration with ML workflows, and performance-aware data consumption. (required)
- Experience with workflow orchestration tools such as Prefect, Airflow, Dagster, or similar. (required)
- Strong experience implementing IaC and CI/CD pipelines for software, data, and machine learning workflows. (required)
- Strong Python engineering skills and experience building maintainable, tested, production-ready code. (required)
- Experience with containerisation using Docker, and ideally deployment on ECS, EKS, Kubernetes, or equivalent platforms. (required)
- Good understanding of model training, batch inference, real-time inference, model monitoring, retraining, and ML lifecycle management. (required)
- Experience working with stakeholders to gather requirements, shape technical solutions, and coordinate delivery across multiple teams. (required)
- Exposure to GenAI, LLMs, AI agents, RAG architectures, prompt orchestration, or enterprise AI assistant implementations. (required)
- Ability to define technical standards, influence architecture, mentor engineers, and guide teams through complex technical decisions. (required)
- Experience with AWS SageMaker, Bedrock, Lambda, ECS, EKS, Step Functions, EventBridge, CloudWatch, IAM, S3, ECR, or related services. (nice-to-have)
- MLflow, model registries, feature stores, model observability, drift detection, and automated retraining patterns. (nice-to-have)
- AIOps use cases such as anomaly detection, incident enrichment, automated ticket creation, event correlation, alert deduplication, or operational intelligence. (nice-to-have)
- Building internal developer platforms, reusable frameworks, project templates, or self-service capabilities for technical teams. (nice-to-have)
- Secure GenAI patterns, including guardrails, access control, PII protection, auditability, and model governance. (nice-to-have)
- Experience in regulated, high-scale, or customer-facing digital environments. (nice-to-have)
- Knowledge of online gaming, entertainment, betting, or high-volume transactional platforms. (nice-to-have)
- 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!
- Chance to turn recognition from leaders and colleagues into amazing prizes.
- Inclusive and supporting community where everyone is celebrated for being themselves.
Entain is one of the world's largest sports betting and gaming entertainment groups and a FTSE 100 company. Formed when GVC Holdings rebranded as Entain in December 2020, its brands trace their history back to the 1880s and include bwin, Coral, Foxy, Gala, Ladbrokes and partypoker. Through its joint venture with MGM Resorts International, it powers BetMGM in the United States with its proprietary technology. Headquartered in London, Entain employs over 30,000 people with offices across 19 countries.