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