Senior Machine Learning Operations (MLOps) Engineer

Placements24; Sandton; On-site; ZAR 1,200,000 - 1,900,000; Full time

Benefits offered by this job

Competitive compensation package

Performance bonuses

Comprehensive benefits (health, life,

Retirement contributions

Paid time off

Job summary

Placements24 is seeking a highly skilled Senior MLOps Engineer to join our clients' advanced technology team in Sandton. This on-site role focuses on bridging ML model development and production deployment, designing and managing the end-to-end ML lifecycle with scalable, reliable infrastructure.

You will collaborate with data scientists and ML engineers to automate training, testing, deployment, and monitoring, implement CI/CD for ML, and optimize cloud infrastructure (AWS, Azure, GCP).

Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• 5+ years of experience in software engineering or DevOps, with a strong focus on MLOps.
• Proven experience in building and managing production ML systems.
• Expertise in cloud platforms (AWS, Azure, or GCP) and their ML services.
• Strong understanding of containerization technologies (Docker, Kubernetes).
• Proficiency in scripting languages such as Python, Bash, or Go.
• Experience with CI/CD tools (e.g., Jenkins, GitLab CI, Argo CD).
• Familiarity with ML frameworks (e.g., TensorFlow, PyTorch) and MLOps tools (e.g., MLflow, Kubeflow).
• Excellent problem-solving, debugging, and system design skills.
• Strong communication and teamwork abilities for an on-site role.

Responsibilities

• Design, build, and maintain scalable MLOps infrastructure and pipelines.
• Automate the ML model lifecycle, including data ingestion, training, validation, deployment, and monitoring.
• Implement CI/CD practices for machine learning models.
• Manage and optimize cloud-based infrastructure (AWS, Azure, GCP) for ML workloads.
• Develop and maintain tools for model versioning, experiment tracking, and feature stores.
• Implement robust monitoring, logging, and alerting systems for ML models in production.
• Collaborate with data scientists and ML engineers to troubleshoot and resolve production issues.
• Ensure the security, reliability, and performance of MLOps systems.
• Stay up-to-date with the latest MLOps tools, technologies, and best practices.

Skills

Problem-solving

Debugging

System design

Communication

Teamwork

Education

Bachelor's or Master's degree in Computer Science or Engineering

Tools

Docker

Kubernetes

Jenkins

GitLab CI

Argo CD

MLflow

Kubeflow

TensorFlow

PyTorch

Python

Job description

About the Role

Our client is seeking a highly skilled Senior Machine Learning Operations (MLOps) Engineer to join their advanced technology team in Sandton. This role is essential for bridging the gap between machine learning model development and production deployment, ensuring our client's AI solutions are scalable, reliable, and efficient. You will be responsible for designing, implementing, and managing the infrastructure and processes required for the end-to-end ML lifecycle. This is an on‑site position, fostering direct collaboration and hands‑on work within a dynamic team environment. The ideal candidate will possess a strong background in software engineering, DevOps principles, and cloud infrastructure, with a specialization in MLOps best practices. You will work closely with data scientists and ML engineers to automate model training, testing, deployment, and monitoring, ensuring smooth and robust operationalization of AI models. Your expertise will be crucial in accelerating the delivery of machine learning innovations.

Key Responsibilities

• Design, build, and maintain scalable MLOps infrastructure and pipelines.
• Automate the ML model lifecycle, including data ingestion, training, validation, deployment, and monitoring.
• Implement CI/CD practices for machine learning models.
• Manage and optimize cloud-based infrastructure (AWS, Azure, GCP) for ML workloads.
• Develop and maintain tools for model versioning, experiment tracking, and feature stores.
• Implement robust monitoring, logging, and alerting systems for ML models in production.
• Collaborate with data scientists and ML engineers to troubleshoot and resolve production issues.
• Ensure the security, reliability, and performance of MLOps systems.
• Stay up-to-date with the latest MLOps tools, technologies, and best practices.

Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• 5+ years of experience in software engineering or DevOps, with a strong focus on MLOps.
• Proven experience in building and managing production ML systems.
• Expertise in cloud platforms (AWS, Azure, or GCP) and their ML services.
• Strong understanding of containerization technologies (Docker, Kubernetes).
• Proficiency in scripting languages such as Python, Bash, or Go.
• Experience with CI/CD tools (e.g., Jenkins, GitLab CI, Argo CD).
• Familiarity with ML frameworks (e.g., TensorFlow, PyTorch) and MLOps tools (e.g., MLflow, Kubeflow).
• Excellent problem‑solving, debugging, and system design skills.
• Strong communication and teamwork abilities for an on‑site role.

Benefits

• Our client offers a competitive salary, performance bonuses, and a comprehensive benefits package, including health insurance, retirement contributions, and paid time off.
• This on‑site role in Sandton provides direct collaboration opportunities within a skilled team.
• We invest in our employees' growth through training programs, access to industry conferences, and opportunities for career advancement.
• Join a company that values innovation, collaboration, and the successful deployment of machine learning solutions.