Job Responsibilities:
- Lead the design and implementation of scalable infrastructure for deploying machine learning models, utilizing Databricks and other cloud platforms.
- Collaborate with data scientists, engineers, and business stakeholders to understand requirements and deliver robust AI solutions.
- Develop and maintain CI/CD pipelines to automate the deployment and management of machine learning models.
- Ensure the scalability, performance, and reliability of deployed models, leveraging cloud infrastructure and best practices.
- Implement governance and security measures to ensure compliance with industry and regulatory standards.
- Stay up-to-date with industry trends and emerging technologies in MLOps, AI engineering, and Databricks.
- Provide training and support to teams on best practices in MLOps, AI deployment, and Databricks usage.
Required Qualifications, Capabilities, and Skills:
- Minimum 8+ years of experience as an MLE
- Extensive experience in ML Ops and AI engineering, with a focus on deploying scalable infrastructure for machine learning models.
- Experience in Databricks and cloud platforms such as AWS, Azure, or Google Cloud.
- Strong programming skills in Python and experience with CI/CD tools.
- Proven experience in leading teams and delivering AI solutions in an enterprise environment.
- Strong understanding of machine learning model deployment patterns and best practices.
Preferred Qualifications, Capabilities, and Skills:
- Experience with big data technologies and frameworks.
- Certification in Databricks, cloud platforms, or AI engineering is a plus.
- Experience working in agile development teams and using Object-Oriented programming languages.