Accrete

Responsibilities:

• Collaborating with data scientists and machine learning engineers to understand their requirements and design scalable, reliable, and efficient machine learning platform solutions.
• Building and maintaining the applications and infrastructure to support end-to-end machine learning workflows, including inference and continual training.
• Developing systems for the definition deployment and operation of the different phases of the machine learning and data life cycles.
• Working within Kubernetes to orchestrate and manage containers, ensuring high availability and fault tolerance of applications.
• Documenting the platform's best practices, guidelines, and standard operating procedures and contributing to knowledge sharing within the team.

Requirements:

• 3+ years of hands-on experience in developing and managing machine learning or data platforms
• Proficiency in programming languages commonly used in machine learning and data applications such as Python, Rust, Bash, Go
• Experience with containerization technologies, such as Docker, and container orchestration platforms like Kubernetes.
• Familiarity with CI/CD pipelines for automated model training and deployment. Basic understanding of DevOps principles and practices.
• Knowledge of data storage solutions and database technologies commonly used in machine learning and data workflows.