Sr Machine Learning Engineer

Job highlights

• Experience working in Agile / Scrum environments
• Bachelors or Masters degree in Computer Science,Computer Applications,or a related technical field. Disclaimer: This job posting has been aggregated from external source
• Required Qualifications
• 4-8 years of hands-on experience building and operating ML / AI systems in production environments

Role Overview

We are looking for a Senior Machine Learning Engineer to join the AI Engineering team, with a primary focus on Hands-On Engineering (MLE) and MLOps & Platform Reliability.

Core Responsibilities

• Build and maintain production-grade ML/AI components and services with minimal supervision.

• Apply software engineering best practices (version control, testing, code review, documentation) across your work.

• Debug and resolve moderately complex issues spanning multiple components of the system.

• Take ownership of small features or workstreams end-to-end, from design through deployment.

• Build and maintain CI/CD pipelines (e.g. GitHub Actions) for ML/AI deployments contribute to pipeline design for new projects.

• Work with Docker, Kubernetes, and Prefect to deploy and orchestrate ML/AI workloads across environments.

• Support models through deployment, monitoring, and retraining escalate drift or degradation issues.

  Key Tools & Technologies

• Cloud & Data Infra: AWS (EC2/ECS, S3, Lambda, IAM, CloudWatch or equivalent) Databricks & Unity Catalog

• Foundational: R Python Git/GitHub software engineering best practices testing SQL

• MLOps & Deployment: Docker, Kubernetes, Prefect CI/CD (GitHub Actions) production monitoring model versioning & lineage GitOps governance

  Required Qualifications

• 4-8 years of hands-on experience building and operating ML/AI systems in production environments.

• Strong proficiency in Python and/or R with a track record of writing clean, testable, production-quality code.

• Demonstrated experience owning CI/CD, containerisation, and orchestration for production ML/AI systems.

• Strong working knowledge of containerisation (Docker), orchestration (Kubernetes), and CI/CD pipelines.

• Working knowledge of AWS cloud services and Databricks/Unity Catalog or equivalent enterprise data platforms.

• Excellent verbal and written communication skills.

• Experience working in Agile/Scrum environments.

  Education

• Bachelors or Masters degree in Computer Science, Computer Applications, or a related technical field.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.