Were looking for an experienced MLOps Engineer to join our team and help design, implement, and maintain scalable machine learning infrastructure and data processing pipelines.
The ideal candidate is passionate about operational excellence, automation, and building reliable systems that empower data scientists and engineers alike.
This role is responsible for enhancing, automating, monitoring, and optimizing data pipelines that collect, transform, cache, index, and manage large-scale datasets.
The ideal candidate is passionate about operational excellence, automation, and building reliable systems that empower data scientists and engineers alike.
This role is responsible for enhancing, automating, monitoring, and optimizing data pipelines that collect, transform, cache, index, and manage large-scale datasets.
Requirements:
5+ years of hands-on experience in MLOps, with a focus on Python-based ML workflows
Experience with containerization and orchestration tools (e.g., Docker, Kubernetes)
Solid understanding of data engineering principles, model serving, and monitoring
Familiarity with cloud-based AI/ML solutions, especially AWS – a strong advantage
Familiarity with Rust – an advantage.
Strong interpersonal skills
Technologically versatile, quick learning
Strong drive to build robust, sustainable solution
5+ years of hands-on experience in MLOps, with a focus on Python-based ML workflows
Experience with containerization and orchestration tools (e.g., Docker, Kubernetes)
Solid understanding of data engineering principles, model serving, and monitoring
Familiarity with cloud-based AI/ML solutions, especially AWS – a strong advantage
Familiarity with Rust – an advantage.
Strong interpersonal skills
Technologically versatile, quick learning
Strong drive to build robust, sustainable solution
This position is open to all candidates.
