Senior AI Engineer - MLOps

Placements24; Noord-Kaap; Hybrid; ZAR 1,000,000 - 1,500,000; Full time

Benefits offered by this job

Hybrid work model

Competitive salary

Professional growth

Job summary

Placements24 in Kimberley, South Africa, invites a Senior AI Engineer specializing in MLOps to join our client in a hybrid role. You will streamline AI development lifecycle, deploy, monitor, and scale ML models while collaborating with data scientists and software engineers.

The ideal candidate has 5+ years in software/DevOps with MLOps focus, strong Python, Docker, Kubernetes, and cloud ML services; enjoy working in a dynamic, innovative environment.

Qualifications

• 5+ years of software engineering or DevOps with a focus on MLOps.
• Proven experience building CI/CD pipelines for ML models.
• Strong cloud experience (AWS, Azure, or GCP) with ML services.
• Proficient in Python and ML frameworks like TensorFlow or PyTorch.

Responsibilities

• Design and maintain scalable MLOps pipelines for training, deployment, monitoring, and retraining.
• Automate the ML lifecycle end-to-end using CI/CD best practices.
• Manage infrastructure for ML model serving with high availability and low latency.
• Implement monitoring and alerting for ML models in production.
• Collaborate with data scientists to optimize models for production deployment.
• Oversee containerization and orchestration of ML workloads (Docker/Kubernetes).
• Ensure security and compliance of ML systems and data.
• Troubleshoot deployment and performance issues in ML models.
• Stay current with MLOps tools, technologies, and best practices.

Skills

MLOps

CI/CD pipelines

Python

Docker

Kubernetes

Cloud platforms

TensorFlow

PyTorch

Scikit-learn

Monitoring

Education

Bachelor's degree in CS/Engineering

Master's degree preferred

Tools

Docker

Kubernetes

Cloud ML services

CI/CD tooling

Job description

About the Role

Our client is a leading innovator in AI & Emerging Technologies and is seeking a highly skilled Senior AI Engineer specializing in MLOps to join their team in Kimberley, Northern Cape, ZA. This hybrid role is crucial for streamlining the AI development lifecycle, ensuring the efficient deployment, monitoring, and scaling of machine learning models. You will be responsible for building and maintaining robust MLOps pipelines, automating workflows, and ensuring the reliability and performance of our AI systems. This position requires a strong blend of software engineering best practices and a deep understanding of machine learning operations. You will work closely with data scientists and software engineers in a collaborative environment, driving operational excellence in our AI initiatives. The Kimberley office provides a supportive setting for this critical role, fostering innovation and cross-functional teamwork. The ideal candidate is proactive, detail-oriented, and passionate about operationalizing AI.

Key Responsibilities

• Design, implement, and maintain scalable MLOps pipelines for model training, deployment, monitoring, and retraining.
• Automate the end-to-end machine learning lifecycle using CI/CD best practices.
• Develop and manage infrastructure for ML model serving, ensuring high availability and low latency.
• Implement robust monitoring and alerting systems for ML models in production.
• Collaborate with data scientists to optimize models for production deployment and performance.
• Manage containerization and orchestration tools (Docker, Kubernetes) for ML workloads.
• Ensure the security and compliance of ML systems and data.
• Troubleshoot and resolve issues related to ML model deployment and performance.
• Stay current with MLOps tools, technologies, and best practices.

Requirements

• Bachelor's degree in Computer Science, Engineering, or a related technical field; Master's degree preferred.
• 5+ years of experience in software engineering or DevOps, with a significant focus on MLOps or ML engineering.
• Proven experience building and managing CI/CD pipelines for machine learning models.
• Strong proficiency with cloud platforms (AWS, Azure, GCP) and their ML services.
• Experience with containerization (Docker) and orchestration (Kubernetes).
• Familiarity with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.
• Knowledge of monitoring tools and techniques for ML systems.
• Proficiency in programming languages like Python.
• Excellent problem-solving, analytical, and communication skills.
• Experience in a hybrid work setting in Kimberley, Northern Cape, ZA or similar.

Benefits

• Competitive salary and performance-related bonuses.
• Comprehensive health, dental, and vision insurance.
• Hybrid work model offering flexibility and work-life balance.
• Opportunities for professional growth and continuous learning.
• Access to modern technology stack and challenging projects.
• Collaborative team environment focused on innovation.
• Generous annual leave and company holidays.