Senior Backend Engineer - MLOps

Job Summary:
We are looking for a Senior Backend Engineer to join the our team. This role focuses on building and operating scalable backend services, data pipelines, and MLOps-enabled systems. The ideal candidate will have strong expertise in Python, Node.js, containerization, databases, and CI/CD, with hands-on experience supporting ML workloads in production. The emphasis is on backend engineering and MLOps enablement for data science platforms.

Job Responsibilities:

Design, develop, and maintain robust backend services using Python and Node.js.

Build and operate containerized applications using Docker and orchestrate workloads using Kubernetes / managed container services.

Develop and manage RESTful APIs for platform services, ML workflows, and internal tools.

Build and maintain data and ML pipelines, including data ingestion, preprocessing, feature preparation, and model serving support.

Implement and manage CI/CD pipelines for backend and ML-related services.

Apply MLOps best practices, including:

Model packaging and deployment

Versioning of models and artifacts

Monitoring, logging, and observability of ML services

Work with databases and storage systems (SQL, NoSQL, object storage) to support platform and ML use cases.

Collaborate with data scientists, ML engineers, and DevOps teams to enable efficient experimentation and reliable production deployments.

Ensure system performance, reliability, scalability, and security across the DS365AI platform.

Continuously improve platform architecture, tooling, and operational practices.

Required Skills:

Strong experience with Python and Node.js for backend development.

Hands-on experience with containerization (Docker) and container orchestration (Kubernetes or managed equivalents).

Solid understanding of databases (PostgreSQL/MySQL, NoSQL, and object storage).

Experience building and maintaining CI/CD pipelines (GitLab CI, GitHub Actions, Azure DevOps, or similar).

Practical knowledge of MLOps concepts and tools, including model deployment, artifact management, and monitoring.

Experience with cloud platforms (AWS and/or Azure).

Strong understanding of backend system design, APIs, and distributed systems.

Nice to Have (Not Core Focus):

Exposure to ML frameworks and workflows (e.g., training pipelines, inference services).

Basic familiarity with LLMs or GenAI platforms (AWS Bedrock, Azure OpenAI) is a plus but not required.

Experience

Minimum: 5–10 years of experience in backend engineering.

Preferred: Experience supporting ML or data science platforms in production environments.

Education / Qualification

Minimum: 16 years of education in Computer Science, Software Engineering, or related field.

Preferred: Master’s degree or equivalent industry experience in backend systems or MLOps.

Location

Islamabad