Lead Engineer - MLOps

November 27

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Code and Theory

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Founded 2011

🤝 B2B

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Description

• Design and implement MLOps pipelines to ensure consistency across the organization. • Configure and manage cloud-based resources (e.g., AWS, GCP, Azure) to support AI/ML workloads, leveraging containerization as needed. • Automate model deployment and management through scripts and tools to streamline the process. • Collaborate with data scientists and engineers to understand their requirements and develop tailored MLOps solutions. • Monitor and optimize AI/ML infrastructure performance by analyzing system performance and identifying bottlenecks. • Stay up-to-date with industry trends and best practices, applying this knowledge to improve our organization's MLOps capabilities.

Requirements

• Extensive experience in deploying machine learning models to cloud environments. • Strong expertise in Docker container orchestration. • Proficiency in Terraform for infrastructure as code (IaC) and cloud resource management. • Hands-on experience with streaming data platforms (e.g., Kafka, Kinesis). • Solid understanding of data cleaning, transformation, and ETL processes. • Experience with CI/CD tools and pipelines (e.g., Jenkins, GitLab CI). • Strong programming skills in Python. Familiarity with ML frameworks (e.g., TensorFlow, PyTorch) is a plus. • Excellent problem-solving skills and the ability to think critically and creatively. • Strong communication skills with the ability to convey technical concepts to non-technical stakeholders.