Dijitprogram - job | Software Engineer

Jobs Description

About the Role
Our team is responsible for building the backend components of MLOps platform on
AWS. The backend components we build are the fundamental blocks for feature
engineering, feature serving, model deployment and model inference in both batch and
online modes.

What you’ll do here
Design & build backend components of our MLOps platform on AWS.
Collaborate with geographically distributed cross-functional teams.
Participate in on-call rotation with the rest of the team to handle production
incidents.

What you’ll need to succeed
Must have skills
Experience with web development frameworks such as FastAPI.
Experience with metaprogramming techniques in Python.
Experience with AWS cloud platform.
Experience with concurrent programming designs such as AsyncIO.
Experience with containers (Docker) and container platorms like AWS ECS or AWS EKS.
Experience with Apache Kafka and developing Kafka client applications in Python.
Strong grasp of data structures and algorithms, with the ability to apply them effectively to solve complex backend challenges.
Proven ability to write clean, efficient, and scalable code, demonstrating solid logical thinking and problem-solving skills.
Good understanding of system design and ability to build scalable and reliable backend systems
Experience with unit and functional testing frameworks.
Experience with CI/CD practices, tools, and frameworks.

Nice to have skills
Experience with MLOps platorms such as AWS Sagemaker, Kubeflow or MLflow
Experience with DevOps & IaC tools such as Terraform, Jenkins etc.
Experience with various Python packaging options such as Wheel, PEX or Conda.

Experience with web development frameworks such as FastAPI.
Experience with metaprogramming techniques in Python.
Experience with AWS cloud platform.
Experience with concurrent programming designs such as AsyncIO.
Experience with containers (Docker) and container platorms like AWS ECS or AWS EKS.
Experience with Apache Kafka and developing Kafka client applications in Python.
Strong grasp of data structures and algorithms, with the ability to apply them effectively to solve complex backend challenges.
Proven ability to write clean, efficient, and scalable code, demonstrating solid logical thinking and problem-solving skills.
Good understanding of system design and ability to build scalable and reliable backend systems
Experience with unit and functional testing frameworks.
Experience with CI/CD practices, tools, and frameworks.

Experience with MLOps platorms such as AWS Sagemaker, Kubeflow or MLflow
Experience with DevOps & IaC tools such as Terraform, Jenkins etc.
Experience with various Python packaging options such as Wheel, PEX or Conda.