Data Engineer at the forefront of AI innovation.
Role Overview:
As a Data Engineer on our GenAI team, you will play a pivotal role in bringing cutting-edge AI models into production. Your expertise will directly contribute to the operational success of advanced AI solutions.
Key Responsibilities:
* Infrastructure Design and Maintenance: Develop and manage robust CI/CD pipelines and cloud infrastructure using Terraform, with a strong focus on reliability, security, and scalability.
* Containerized ML Applications: Manage containerized ML applications with Docker; familiarity with Kubernetes is a plus.
* ML Lifecycle Support: Monitor model performance, optimize infrastructure, and share best practices across the team to foster continuous improvement.
The ideal candidate has 3-5 years of experience as a data engineer, DevOps engineer or in a similar role. They possess programming expertise in Python in a machine learning or data context, strong knowledge of Docker and cloud infrastructure, and experience with Azure is a plus. Experience in a data engineering context is a plus, though heavy ETL is not the focus.
Bonus points are given for experience with MLOps tools, knowledge of security best practices in cloud-based ML environments, and interest in or experience with GenAI, LLMs, or prompt engineering.
As a member of the GenAI team, you will collaborate closely with data scientists and ML engineers to bring innovative AI solutions to market.