MLOPs Engineer

Engineering & Technical, Information Technology (IT)
Africa
August 20, 2025
Hybrid
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Job Description

We are seeking a highly skilled MLOPs Engineer with deep experience in building and maintaining scalable machine learning infrastructure. This role requires a strong background in Google Cloud Platform (GCP) and hands-on expertise in automating ML workflows using tools like Vertex AI, Docker, and Dagster.

As an MLOPs Engineer, you will work closely with data scientists, software engineers, and DevOps teams to ensure seamless model development, deployment, and monitoring across production environments.

Key Responsibilities

  • Design and implement robust, scalable MLOps pipelines using GCP, Vertex AI, and Dagster.
  • Collaborate with data science teams to produce ML models and ensure reproducibility.
  • Define and manage ML infrastructure architecture in GCP. Automate model training, validation, deployment, and monitoring.
  • Support CI/CD for ML projects and maintain containerised environments using Docker.
  • Identify and resolve infrastructure bottlenecks and system-level challenges.
  • Execute low-level technical tasks including debugging, scripting, and pipeline optimisation.

Qualification

  • Senior-level experience with Google Cloud Platform (GCP).
  • In-depth understanding of cloud architecture and best practices for scalable ML solutions.
  • Strong hands-on experience with Vertex AI and containerization tools such as Docker.
  • Experience with orchestration tools such as Dagster (or alternatives like Airflow, Prefect).
  • Proficient in Python and scripting for automation and workflow management.
  • Ability to translate high-level architectural decisions into executable tasks.
  • Excellent problem-solving and communication skills.

Must Have:

  • Experience in CI/CD pipelines for ML (e.g., GitHub Actions, Cloud Build).
  • Familiarity with ML model monitoring and drift detection.
  • Prior experience working in cross-functional teams in fast-paced environments.

 Perks

  • Competitive salary commensurate with qualification and experience
  • Pension benefits
  • Bonuses and end-of-year package
  • Medical insurance, with dependents
  • Internet data allocation for remote work
  • Employee bonding activities (bi-monthly happy hour, sporting activities)

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