Senior AI Software Engineer - MLOps

Placements24; Graafwater; Hybrid; ZAR 1,976,000 - 2,635,000; Full time

Benefits offered by this job

Remote work flexibility

Health benefits

Professional development budget

Job summary

Placements24 is seeking a Senior AI Software Engineer with a strong MLOps focus to design and deploy scalable ML pipelines. This remote role emphasizes building robust infrastructure, automation, and end-to-end model lifecycle management.

You’ll collaborate with data scientists and software engineers to operationalize AI at scale. The ideal candidate has 5+ years of software engineering experience, strong Python skills, and hands-on MLOps tooling expertise.

Qualifications

• 5+ years of software engineering experience with a focus on MLOps/AI infrastructure.
• Proficiency in Python and cloud platforms (AWS, Azure, GCP).
• Hands-on experience with MLOps tools and frameworks (Kubeflow, MLflow, Docker, Kubernetes, Terraform).
• Strong understanding of CI/CD principles applied to ML pipelines.
• Experience with monitoring and logging tools for distributed systems.
• Familiarity with ML concepts and model lifecycle management.
• Excellent problem-solving and debugging skills.
• Strong communication and collaboration in a remote team.

Responsibilities

• Design, build, and maintain scalable MLOps pipelines for ML models.
• Automate deployment, monitoring, and management of AI/ML models in production.
• Develop and implement CI/CD processes for ML workflows.
• Collaborate with data scientists and software engineers for model integration.
• Optimize ML infrastructure for performance, cost, and reliability.
• Implement best practices for model versioning, testing, and validation.
• Set up monitoring and alerting for AI/ML models in production.
• Troubleshoot deployment and performance issues of ML models.
• Contribute to design and architecture of the AI platform.
• Stay current with MLOps tools and industry best practices.

Skills

Python programming

CI/CD for ML

Distributed systems

Education

Bachelor's or Master's in CS/Engineering

Tools

Kubeflow

MLflow

Docker

Kubernetes

Terraform

Job description

About the Role

Our client is seeking a highly skilled Senior AI Software Engineer with expertise in MLOps to join their cutting-edge team. This is a fully **remote** position, allowing you to contribute to groundbreaking AI projects from anywhere. The focus will be on building robust, scalable, and efficient machine learning pipelines and infrastructure. You will play a critical role in operationalizing AI models, ensuring their seamless deployment, monitoring, and maintenance. This is an exceptional opportunity to work with state-of-the-art technologies and shape the future of AI deployment. We are looking for a passionate individual who thrives in a **remote-first** environment and is dedicated to advancing the field of MLOps. Our client is committed to fostering a collaborative and innovative remote work culture.

Key Responsibilities

• Design, build, and maintain scalable MLOps pipelines for machine learning models.
• Automate the deployment, monitoring, and management of AI/ML models in production.
• Develop and implement CI/CD processes for machine learning workflows.
• Collaborate with data scientists and software engineers to ensure smooth model integration.
• Optimize ML infrastructure for performance, cost, and reliability.
• Implement best practices for model versioning, testing, and validation.
• Set up monitoring and alerting systems for AI/ML models in production.
• Troubleshoot and resolve issues related to ML model deployment and performance.
• Contribute to the design and architecture of the overall AI platform.
• Stay current with MLOps tools, technologies, and industry best practices.

Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, or a related quantitative field.
• 5+ years of experience in software engineering, with a significant focus on MLOps and AI/ML infrastructure.
• Proficiency in Python and experience with cloud platforms (AWS, Azure, GCP).
• Hands-on experience with MLOps tools and frameworks (e.g., Kubeflow, MLflow, Docker, Kubernetes, Terraform).
• Strong understanding of CI/CD principles and their application to ML pipelines.
• Experience with monitoring and logging tools for distributed systems.
• Familiarity with machine learning concepts and model lifecycle management.
• Excellent problem-solving and debugging skills.
• Strong communication and collaboration skills, essential for a **remote** team.
• Proven ability to work independently and manage tasks effectively in a **remote** setting.

Benefits

This fully **remote** position offers a competitive salary, comprehensive health benefits, and a generous bonus structure. Employees have access to continuous learning opportunities, including online courses, workshops, and funding for certifications. Enjoy the ultimate flexibility of working from your preferred location while contributing to exciting AI projects. Our client values a healthy work-life balance and provides a supportive online community for all team members. Opportunities for career growth and advancement within a leading AI organization are abundant.