The Role: A leading technology organization is seeking a Machine Learning Ops Engineer to help build and maintain robust ML platforms. You’ll work in a collaborative, innovative environment with opportunities for professional growth and exposure to the latest cloud and AI tools.
Key Responsibilities
* Design, develop, and maintain scalable ML infrastructure on AWS.
* Integrate ML models into production systems in partnership with DevOps and infrastructure teams.
* Enhance platform performance, reliability, and scalability.
* Extend and optimise ML frameworks and libraries.
* Implement monitoring and governance for deployed models.
* Set and uphold technical standards and best practices.
Required Skills
* Strong hands-on experience with AWS (EC2, S3, Lambda, SageMaker).
* Proficient in Python (or similar languages).
* Familiarity with ML Ops and platform engineering concepts.
* Experience with data pipeline tools (e.g., Apache Airflow, AWS Glue).
* Skilled in DevOps tools (Git, Jenkins, GitHub Actions).
* Experience with Docker and Kubernetes.
* Advantageous: Knowledge of Groovy, Azure OpenAI, Langgraph, Bedrock.
* Strong analytical and communication skills.
Preferred Qualifications
* AWS certifications (Solutions Architect or Machine Learning).
* Experience with CI/CD and big data technologies (Spark, Hadoop).
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