Senior Machine Learning Operations (MLOps) Engineer

Placements24; Upington; Hybrid; ZAR 1,000,000 - 1,800,000; Full time

Benefits offered by this job

Health insurance

Dental insurance

Vision insurance

Retirement plan

Paid time off

Professional development budget

Remote work

Job summary

Placements24 is seeking a Senior MLOps Engineer to design, deploy, and monitor scalable ML infrastructure in a fully remote setup. You will bridge data science and IT operations to ensure robust ML model deployment and operational excellence across cloud platforms.

The role requires a strong software engineering background, expertise in MLOps, and hands-on experience with AWS/Azure/GCP, Docker/Kubernetes, and IaC tools. Join a fast-paced team driving AI-driven analytics remotely.

Qualifications

• BS in Computer Science, Engineering or related field; MS a plus.
• 5+ years in software engineering/DevOps, with ≥3 years in MLOps or ML cloud infra.
• Proficiency in Python; Bash scripting experience.
• Hands-on with cloud platforms (AWS/Azure/GCP) and ML services.

Responsibilities

• Design and manage CI/CD pipelines for ML models.
• Build and maintain scalable ML training, deployment, and serving infra.
• Implement monitoring, logging and alerting for ML in production.
• Automate ML lifecycle: data validation, training, testing, deployment.
• Collaborate with data scientists and engineers to streamline ML workflows.
• Ensure reliability, scalability, and security of ML systems and infra.
• Optimize cloud resources for ML workloads; troubleshoot issues.
• Stay current with emerging MLOps tools and best practices.

Skills

Python

Shell scripting

Cloud platforms

Docker/Kubernetes

CI/CD tools

IaC (Terraform/Ansible)

ML frameworks

Communication & problem solving

Education

Bachelor's in CS/Engineering

Master's degree preferred

Tools

Docker

Kubernetes

Terraform

Ansible

GitHub Actions

Jenkins

Job description

About the Role

Our client, a pioneering force in AI-driven analytics, is seeking a highly skilled Senior Machine Learning Operations (MLOps) Engineer to join their dynamic and fully remote team. This role is essential for building and maintaining the infrastructure and processes required to deploy, monitor, and manage machine learning models at scale. You will bridge the gap between data science and IT operations, ensuring seamless integration and efficient performance of ML systems. The ideal candidate has a robust background in software engineering, cloud infrastructure, and a deep understanding of the machine learning lifecycle. This is an exceptional opportunity to drive operational excellence in AI and contribute to innovative projects from anywhere, supporting our clients' advanced analytical capabilities.

Key Responsibilities

• Design, implement, and manage robust CI/CD pipelines for machine learning models.
• Develop and maintain scalable infrastructure for training, deploying, and serving ML models.
• Implement monitoring, logging, and alerting systems for ML models in production.
• Automate the ML lifecycle, including data validation, model training, testing, and deployment.
• Collaborate with data scientists and software engineers to streamline the ML development and deployment process.
• Ensure the reliability, scalability, and security of ML systems and infrastructure.
• Manage and optimize cloud resources (e.g., AWS, Azure, GCP) for ML workloads.
• Troubleshoot and resolve issues related to ML model performance and infrastructure.
• Stay current with emerging MLOps tools, technologies, and best practices.

Requirements

• Bachelor's degree in Computer Science, Engineering, or a related field; Master's degree is a plus.
• 5+ years of experience in software engineering or DevOps, with at least 3 years focused on MLOps or cloud infrastructure for ML.
• Proficiency in programming languages such as Python and experience with scripting languages (e.g., Bash).
• Hands-on experience with cloud platforms (AWS, Azure, or GCP) and their relevant ML services.
• Expertise in containerization technologies (Docker, Kubernetes).
• Experience with CI/CD tools (e.g., Jenkins, GitLab CI, GitHub Actions).
• Familiarity with ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and ML model serving technologies (e.g., TensorFlow Serving, Seldon Core).
• Strong understanding of infrastructure as code (IaC) principles and tools (e.g., Terraform, Ansible).
• Excellent problem-solving and communication skills.

Benefits

Our client offers a highly competitive salary, comprehensive health, dental, and vision insurance, generous retirement contributions, and ample paid time off. This fully remote position provides the ultimate flexibility. We invest in our employees' professional development through access to online courses, training programs, and conference attendance budgets. You will work with cutting-edge technologies and contribute to impactful AI projects in a collaborative, innovation-driven environment. Our client values a healthy work-life balance and fosters a culture of continuous learning and growth, making this an ideal opportunity for an experienced MLOps engineer.