Senior Machine Learning Engineer - MLOps

Placements24; Richards Bay; Hybrid; ZAR 1,000,000 - 1,600,000; Full time

Benefits offered by this job

Medical aid

Retirement fund contributions

Hybrid work model

Job summary

Placements24 is seeking a Senior Machine Learning Engineer (MLOps) to extend its AI capabilities in Richards Bay, KwaZulu-Natal. You will bridge model development and production, designing robust pipelines and infrastructure for scalable deployments.

The role emphasizes cloud-native ML, CI/CD for ML, and collaboration with data scientists to accelerate iteration. Ideal candidates have 4+ years in ML engineering with MLOps, strong Python skills, and hands-on experience with Kubeflow, MLflow, TFX

Qualifications

• Bachelor's or Master's in CS/Engineering or related field.
• 4+ years in Machine Learning Engineering with MLOps focus.
• Strong Python and ML libraries experience.
• Experience with MLOps tools and cloud platforms.
• Proficient in CI/CD for ML, data pipelines, and distributed computing.

Responsibilities

• Design and maintain scalable MLOps pipelines for training, validation, deployment and monitoring.
• Develop infrastructure for ML workloads on cloud and container platforms.
• Implement CI/CD practices for ML models.
• Collaborate with data scientists to streamline model lifecycle.
• Automate data validation, feature pipelines, and retraining processes.
• Monitor models for drift and performance, with corrective actions.

Skills

Python

CI/CD

Problem solving

Collaboration

ML deployment

Teamwork

Education

Bachelor's in CS or related field

Master's preferred

Tools

Kubeflow

MLflow

TFX

Seldon Core

AWS

Azure

GCP

Docker

Kubernetes

Python libraries (scikit-learn, TensorFlow, PyTorch)

Job description

About the Role

Our client is expanding its cutting-edge AI capabilities and is looking for a highly skilled Senior Machine Learning Engineer specializing in MLOps to join their team in **Richards Bay, KwaZulu-Natal**. This role is critical for bridging the gap between machine learning model development and production deployment, ensuring our AI solutions are scalable, reliable, and efficient. You will play a key part in designing, implementing, and maintaining robust MLOps pipelines and infrastructure, enabling faster iteration and deployment of machine learning models. This is an exciting opportunity to contribute to impactful projects within the growing AI sector in **Richards Bay, KwaZulu-Natal**. If you are passionate about operationalizing machine learning at scale, this is the role for you.

Key Responsibilities

• Design, build, and maintain scalable and robust MLOps pipelines for automated model training, validation, deployment, and monitoring.
• Develop and manage infrastructure for machine learning workloads, utilizing cloud platforms and containerization technologies.
• Implement CI/CD practices tailored for machine learning models.
• Collaborate with data scientists and ML engineers to streamline the model development lifecycle.
• Develop tools and frameworks to enhance the efficiency and reliability of ML deployments.
• Monitor deployed models for performance degradation, drift, and anomalies, and implement corrective actions.
• Ensure the security, compliance, and governance of ML systems.
• Automate data validation, feature engineering pipelines, and model retraining processes.

Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, or a related quantitative field.
• Proven experience (4+ years) in Machine Learning Engineering, with a strong focus on MLOps.
• Proficiency in programming languages such as Python and associated ML libraries (e.g., scikit-learn, TensorFlow, PyTorch).
• Hands‑on experience with MLOps tools and platforms (e.g., Kubeflow, MLflow, TFX, Seldon Core).
• Expertise in cloud platforms (AWS, Azure, GCP) and container orchestration (Docker, Kubernetes).
• Strong understanding of CI/CD principles and practices.
• Experience with data pipelines, ETL processes, and distributed computing frameworks.
• Excellent problem-solving skills and the ability to work effectively in a collaborative team environment.

Benefits

• Our client offers a competitive salary and a comprehensive benefits package, including medical aid and retirement fund contributions.
• This position provides excellent opportunities for professional growth and development in the rapidly evolving field of MLOps.
• You will work with a talented team on challenging projects and have access to modern tools and technologies.
• The hybrid work model allows for a blend of in-office collaboration and remote flexibility.
• Our client is committed to fostering a positive work environment and promoting work‑life balance.
• Be part of a forward‑thinking company making significant strides in AI in **Richards Bay, KwaZulu-Natal**.