About the Role

We are building the backend components of our MLOps platform on AWS. These components form the foundation for feature engineering, feature serving, model deployment, and model inference in both batch and online modes.

Responsibilities

• Design and build backend components of the MLOps platform on AWS.

• Collaborate with geographically distributed cross-functional teams.

• Participate in on-call rotation to handle production incidents.

Must-Have Skills

• Strong experience with Python and web frameworks such as FastAPI.

• Expertise in metaprogramming techniques in Python.

• Hands-on experience with AWS cloud platform.

• Knowledge of concurrent programming (AsyncIO).

• Experience with Docker and container orchestration platforms (AWS ECS/EKS).

• Proficiency with Apache Kafka and developing Kafka client applications in Python.

• Strong grasp of data structures and algorithms with practical problem-solving ability.

• Ability to write clean, efficient, and scalable code.

• Good understanding of system design for scalable and reliable backend systems.

• Experience with unit/functional testing frameworks.

• Familiarity with CI/CD practices, tools, and frameworks.

Nice-to-Have Skills

• Experience with MLOps platforms such as AWS Sagemaker, Kubeflow, or MLflow.

• Knowledge of DevOps & Infrastructure as Code (IaC) tools such as Terraform, Jenkins.

Familiarity with Python packaging (Wheel, PEX, Conda).

Mandatory Skills:

Good to have skills