Machine Learning Operations Engineer (MLOps)

My client is looking for an experienced Machine Learning Operations Engineer to join their growing team. They are looking for a Machine Learning Engineer with a solid background in Cloud Engineering with a focus on platform engineering. You’ll develop machine learning platforms and ensure the continuous deployment and operation of Machine Learning models through effective infrastructure and tooling.

The Role

You’ll Lead the Design, build, and maintain scalable, reliable, and efficient Machine Learning platforms, ensuring robust performance and operational excellence. Work with infrastructure and DevOps teams to integrate Machine Learning models into the broader platform to ensure continuous operation and scaling. Improve the architecture, scalability, stability, and performance of the Machine Learning platform, focusing on AWS cloud engineering solutions and platform services.

Develop processes for model monitoring and governance, ensuring successful ML model operationalization and compliance with industry standards on the platform. Develop and extend existing machine learning libraries and frameworks to enhance model performance and integrate them effectively within the platform.

Define objectives for the Machine Learning platform, own the technical roadmap, and be accountable for delivering results that align with platform engineering goals. Define and uphold standards for platform engineering and operational excellence, striving to run best-in-class ML platforms and continually improving them to incorporate the latest innovations. Design and implement architectural best practices specifically for platform engineering, ensuring efficient and scalable deployment of ML solutions.

Skills/Experience Needed

Hands on experience in Cloud Engineering, particularly in AWS services such as EC2, S3, Lambda and SageMaker. Proficiency in platform engineering practices and frameworks for machine learning operations (MLOps).

Good hands on experience development skills in Python or other relevant languages. Experience with DevOps tools such as Git, Jenkins, GitHub Actions or similar. Experience with data pipeline tools such as Apache Airflow, AWS Glue, or similar.

Experience with containerization and orchestration tools like Docker and Kubernetes. Familiarity with Groovy is an added advantage. Knowledge of Azure OpenAI, Langgraph, Bedrock an advantage. Good communication skills and able to work collaboratively.

Good to have (not a must have!) AWS Certified Solutions Architect or AWS Certified Machine Learning specialty. Exposure to CI/CD tools and practices. Some experience with Groovy is an advantage. Knowledge of big data technologies such as Apache Spark or Hadoop.

Permanent role. Hybrid 3 days a week in Letterkenny, Co. Donegal. They offer competitive salaries, including bonus, pension, health care, life insurance, laptop, phone, access to extensive training resources, company discounts, on site parking and other.

You must be eligible to work in Ireland/EU.

Please do not hesitate to Contact David Coyle at 01 6351748 or email david@methodius.com