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Machine learning operations engineer (mlops)

Letterkenny
Methodius Ltd
Operations engineer
Posted: 5 June
Offer description

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

The Role Lead the design, build, and maintenance of scalable, reliable, and efficient Machine Learning platforms, ensuring robust performance and operational excellence. Collaborate with infrastructure and DevOps teams to integrate Machine Learning models into the broader platform for continuous operation and scaling. Improve 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. Extend existing machine learning libraries and frameworks to enhance performance and integration within the platform. Define objectives for the Machine Learning platform, own the technical roadmap, and ensure alignment with platform engineering goals. Establish and uphold standards for platform engineering and operational excellence, striving for best-in-class ML platforms. Design and implement architectural best practices for efficient and scalable deployment of ML solutions. Skills/Experience Needed Hands-on experience in Cloud Engineering, especially with AWS services such as EC2, S3, Lambda, and SageMaker. Proficiency in platform engineering practices and frameworks for MLOps. Development skills in Python or relevant languages. Experience with DevOps tools such as Git, Jenkins, GitHub Actions, or similar. Experience with data pipeline tools like Apache Airflow, AWS Glue, or similar. Experience with containerization and orchestration tools like Docker and Kubernetes. Familiarity with Groovy is an advantage. Knowledge of Azure OpenAI, Langgraph, Bedrock is a plus. Good communication skills and ability to work collaboratively. Additional Preferences AWS Certified Solutions Architect or AWS Certified Machine Learning specialty is advantageous. Exposure to CI/CD tools and practices. Experience with big data technologies such as Apache Spark or Hadoop. Additional Information This is a permanent role with a hybrid work model (3 days a week in Letterkenny, Co. Donegal).
The package includes competitive salary, bonus, pension, healthcare, life insurance, laptop, phone, extensive training resources, company discounts, on-site parking, and more.

You must be eligible to work in Ireland/EU.

Contact David Coyle at 01 6351748 or email ******.

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Machine learning operations engineer (mlops)
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