Principal Machine Learning Engineer - MLOps

Placements24; Pretoria; Hybrid; ZAR 1,000,000 - 2,000,000; Full time

Benefits offered by this job

Fully remote work

Performance bonus

Job summary

Placements24 is seeking a Principal Machine Learning Engineer (MLOps) for a fully remote role. You will architect robust ML pipelines, deploy and monitor models, and optimize cloud-based ML infrastructure across AWS, GCP, and Azure.

You will lead CI/CD for ML, collaborate with data scientists and software engineers, and mentor junior colleagues while keeping up with evolving MLOps practices.

Qualifications

• Master's or Ph.D. in CS/SE or related quantitative field.
• 8+ years in software or ML engineering with MLOps focus.
• Experience designing end-to-end ML pipelines.
• Proficiency with cloud platforms and containerization tools.
• Experience with CI/CD tools and IaC (Terraform/Ansible).
• Strong ML concepts knowledge and ability to work remotely.

Responsibilities

• Design and maintain scalable MLOps infrastructure and workflows.
• Develop CI/CD pipelines for ML models with testing, deployment, monitoring.
• Collaborate with data scientists to operationalize models.
• Implement model monitoring, drift detection, and performance tracking.
• Manage cloud-based ML infra (AWS SageMaker, GCP, Azure ML).
• Create automation scripts to improve ML lifecycle efficiency.
• Ensure security, scalability, and cost-effectiveness of deployments.
• Mentor junior engineers and share knowledge.
• Stay updated on latest MLOps tools and best practices.

Skills

MLOps

CI/CD

Cloud platforms

Python

Docker

Kubernetes

Terraform

Ansible

Jenkins

Monitoring

Communication

Education

Master's degree

PhD

Tools

AWS

GCP

Azure

Job description

About the Role

Our client, a dynamic technology firm at the forefront of AI innovation, is seeking an exceptional Principal Machine Learning Engineer specializing in MLOps to join their rapidly expanding team. This is a fully remote position, offering the opportunity to architect and implement robust, scalable, and efficient machine learning operations pipelines. You will be instrumental in bridging the gap between machine learning research and production deployment, ensuring that models are deployed, monitored, and managed effectively. The ideal candidate possesses deep expertise in MLOps best practices, cloud infrastructure, and continuous integration/continuous deployment (CI/CD) for machine learning. You will work closely with data scientists and software engineers to automate and streamline the ML lifecycle, driving the successful operationalization of cutting-edge AI solutions. This role is perfect for a seasoned professional looking to make a significant impact in a challenging and rewarding environment.

Key Responsibilities

• Design, build, and maintain scalable and reliable MLOps infrastructure and workflows.
• Develop and implement CI/CD pipelines for machine learning models, including automated testing, deployment, and monitoring.
• Collaborate with data scientists to operationalize machine learning models, ensuring they are production-ready.
• Implement strategies for model monitoring, performance tracking, and drift detection in production environments.
• Manage and optimize cloud-based ML infrastructure (e.g., AWS SageMaker, GCP AI Platform, Azure ML).
• Develop automation tools and scripts to improve the efficiency of the ML lifecycle.
• Ensure the security, scalability, and cost-effectiveness of ML deployments.
• Mentor junior engineers and contribute to the team's technical growth and knowledge sharing.
• Stay up-to-date with the latest MLOps tools, techniques, and best practices.

Requirements

• Master's or Ph.D. in Computer Science, Software Engineering, or a related quantitative field.
• Minimum of 8 years of experience in software engineering or machine learning engineering, with a strong focus on MLOps.
• Proven experience designing and implementing end-to-end ML pipelines.
• Expertise in cloud platforms (AWS, GCP, Azure) and containerization technologies (Docker, Kubernetes).
• Proficiency in scripting languages such as Python and experience with infrastructure-as-code tools (e.g., Terraform, Ansible).
• Strong understanding of machine learning concepts and algorithms.
• Experience with CI/CD tools (e.g., Jenkins, GitLab CI, GitHub Actions).
• Excellent problem-solving, analytical, and communication skills.
• Ability to work independently and collaboratively in a remote team environment.
• Experience with monitoring and logging tools (e.g., Prometheus, Grafana, ELK stack).

Benefits

This position offers a fully remote work arrangement, providing ultimate flexibility. Our client provides a highly competitive salary, comprehensive health and wellness benefits, and a performance-driven bonus scheme. Continuous professional development is encouraged through dedicated learning budgets and access to cutting-edge resources. You will have the opportunity to work on challenging and impactful projects with a team of talented professionals, driving the future of AI operationalization. Join us from anywhere and contribute to groundbreaking work, even though our team is based in Pretoria, Gauteng.