Qualifications

• Extensive experience as a Machine Learning Engineer, MLOps Engineer, AI Platform Engineer, or similar role.
• Proven track record designing and operating production-grade ML infrastructure and MLOps platforms.
• Strong hands-on experience with AWS cloud services related to ML, orchestration, compute, storage, and security.
• Experience working with Snowflake as a data platform, including data integration and performance optimization.
• Proficiency with workflow orchestration tools such as Prefect, Airflow, or Dagster.
• Expertise in implementing Infrastructure as Code (IaC) and CI/CD pipelines for data, software, and ML workflows.
• Strong Python programming skills, with experience in building maintainable, tested, and production-ready code.
• Experience with containerization technologies such as Docker and deployment on ECS, EKS, or Kubernetes.
• Deep understanding of ML lifecycle management, including model training, inference, monitoring, and retraining.
• Ability to collaborate effectively with stakeholders to gather requirements and deliver technical solutions.
• Exposure to GenAI, LLMs, AI agents, and enterprise AI applications is desirable.

Responsibilities

• Lead the design and implementation of scalable MLOps and AIOps frameworks that streamline ML development, deployment, and monitoring processes.
• Build and maintain reusable ML infrastructure components utilizing AWS services, Snowflake, Prefect, and other enterprise tools.
• Provide technical leadership and mentorship across ML engineering initiatives, ensuring solutions are robust, secure, and scalable.
• Support the development of ML platform capabilities, including experimentation, orchestration, deployment, incident management, and governance.
• Collaborate closely with Data Scientists, Data Engineers, Cloud Engineers, Product Owners, and business stakeholders to translate requirements into practical technical solutions.
• Contribute to the design and deployment of GenAI and LLM-based solutions, including enterprise AI assistants and automation workflows.
• Create frameworks, templates, standards, and reference implementations to accelerate delivery and reduce duplication across teams.
• Promote modern software engineering practices such as automated testing, CI/CD, containerization, and infrastructure as code.
• Support orchestration and automation of ML workloads using tools like Prefect, AWS-native services, and event-driven architectures.
• Define architectural standards and technical roadmaps for ML infrastructure, MLOps, AIOps, and GenAI capabilities.
• Review technical designs and code, mentor engineers, and uphold high engineering standards across the team.
• Identify operational risks, technical debt, and platform limitations, proposing pragmatic solutions for continuous improvement.

Benefits

• Competitive salary package with performance-based incentives.
• Option to buy, sell, or carry over annual leave, including additional days off during Christmas and New Year.
• Opportunities for professional growth and development within a global organization.
• Inclusive and collaborative work environment that values diversity and individual contributions.
• Supportive community with recognition programs and rewarding incentives.
• Flexible working arrangements and accommodations to support your needs.

Equal Opportunity

Entain is committed to creating an inclusive environment where all employees are valued and respected. We are an equal opportunity employer and do not discriminate based on race, gender, age, religion, sexual orientation, disability, or any other protected characteristic. We encourage applications from diverse backgrounds and are dedicated to fostering a workplace that reflects the communities we serve. If you require any accommodations during the recruitment process, please contact us, and we will be happy to assist.