Description

You will design, build, and maintain scalable machine learning systems and model serving infrastructure.

This role is on-site.

Responsibilities

• Design and implement scalable model serving infrastructure, APIs, and data pipelines for production use.
• Develop, evaluate, and optimize machine learning models and inference pipelines for performance and reliability.
• Write high-quality, well-tested code, contribute to code reviews, and maintain CI/CD practices.
• Refactor existing systems to improve maintainability, resiliency, and scalability.
• Drive best practices in data governance, model validation, monitoring, and incident response.

Required Skills

• 3-5+ years of professional software engineering experience with significant machine learning exposure.
• Proficiency in Python and experience with ML frameworks such as PyTorch or TensorFlow.
• Experience building and deploying services on cloud platforms (AWS, GCP, or Azure).
• Hands-on experience with container orchestration using Kubernetes and Docker.
• Strong understanding of distributed systems, system design, caching, and data modelling.
• Familiarity with Java, Kotlin, or Go is a plus.
• Hands-on experience with model serving, feature stores, and observability tools.
• Experience with CI/CD, automated testing, and debugging in production environments.

Preferred Skills

• Experience mentoring colleagues and sharing knowledge across the engineering organization.
• Bachelor's degree in Computer Science or related field.

Key Skills

Education

Bachelor's degree