Lead AI/ML Operations (MLOps) Engineer

Placements24; East London; Hybride; ZAR 1 000 000 - 1 800 000; Plein temps

Avantages offerts par ce poste

Competitive salary

Bonus potential

Medical, dental, retirement plans

Remote work environment

Training resources and conferences

Résumé du poste

Placements24 is seeking a Lead AI/ML Operations Engineer to establish and scale MLOps practices in a fully remote role. You will deploy, monitor, and manage ML models in production, define CI/CD for ML workflows, and lead a team to build robust ML operational systems.

The ideal candidate has 6+ years in software/DevOps with 4+ years in MLOps, strong cloud experience (AWS/Azure/GCP), and expertise in Docker/Kubernetes, Terraform, and IaC. Remote work experience is highly valued.

Qualifications

• Master's or Bachelor's degree in Computer Science, Software Engineering, or a related technical field.
• 6+ years in software engineering or DevOps, with at least 4 years focused on MLOps or ML infrastructure.
• Deep expertise in building and managing CI/CD pipelines for machine learning.
• Strong experience with cloud platforms (AWS, Azure, or GCP) and their ML services.
• Proficiency with containerization (Docker) and orchestration (Kubernetes).
• Experience with infrastructure as code (IaC) tools like Terraform or CloudFormation.
• Solid understanding of machine learning concepts, algorithms, and the ML lifecycle.
• Proficiency in scripting languages such as Python or Bash.
• Experience with monitoring and logging tools (Prometheus, Grafana, ELK stack).
• Excellent problem-solving, communication, and leadership skills.
• Experience in a fully remote work environment is highly desirable.

Responsabilités

• Design, implement, and maintain robust MLOps pipelines for model training, validation, deployment, and monitoring.
• Develop and automate infrastructure provisioning for ML environments using Terraform or CloudFormation.
• Implement CI/CD for machine learning models.
• Manage and optimize containers/orchestration platforms (Docker, Kubernetes).
• Establish monitoring, logging, and alerting systems for ML models in production.
• Collaborate with data scientists and ML engineers to streamline the model development lifecycle.
• Ensure scalability, reliability, security, and cost-effectiveness of ML infrastructure.
• Define and enforce best practices for version control, testing, and documentation of ML artifacts.
• Troubleshoot and resolve production issues related to ML systems.
• Mentor junior engineers and foster a culture of operational excellence in ML.
• Stay current with emerging MLOps tools and best practices.

Connaissances

CI/CD workflows

ML concepts

Python scripting

Leadership

Remote work

Problem solving

Formation

Bachelor's or Master's in CS/Software Engineering

Outils

Terraform

CloudFormation

Docker

Kubernetes

Prometheus

Grafana

ELK stack

Python

Bash

Description du poste

About the Role

Our client, a trailblazer in the AI & Emerging Technologies field, is seeking a highly experienced Lead AI/ML Operations (MLOps) Engineer to establish and scale their MLOps practices. This is a critical, fully remote role designed to ensure the seamless deployment, monitoring, and management of machine learning models in production environments. You will be instrumental in defining and implementing best practices for CI/CD, automation, and infrastructure management specific to ML workflows. The ideal candidate possesses a strong background in both software engineering/DevOps and machine learning, with a proven ability to build robust and scalable ML operational systems. This is an exceptional opportunity to shape the operational backbone of a cutting-edge AI organization from the ground up.

Key Responsibilities

• Design, implement, and maintain robust MLOps pipelines for model training, validation, deployment, and monitoring.
• Develop and automate infrastructure provisioning for ML environments using tools like Terraform or CloudFormation.
• Implement continuous integration and continuous delivery (CI/CD) for machine learning models.
• Manage and optimize containerization and orchestration platforms (Docker, Kubernetes).
• Establish comprehensive monitoring, logging, and alerting systems for ML models in production.
• Collaborate with data scientists and ML engineers to streamline the model development and deployment lifecycle.
• Ensure the scalability, reliability, security, and cost-effectiveness of ML infrastructure.
• Define and enforce best practices for version control, testing, and documentation of ML artifacts.
• Troubleshoot and resolve production issues related to ML systems.
• Mentor junior engineers and foster a culture of operational excellence in ML.
• Stay current with emerging MLOps tools, technologies, and best practices.

Requirements

• Master's or Bachelor's degree in Computer Science, Software Engineering, or a related technical field.
• Minimum of 6 years of experience in software engineering or DevOps, with at least 4 years focused specifically on MLOps or ML infrastructure.
• Deep expertise in building and managing CI/CD pipelines for machine learning.
• Strong experience with cloud platforms (AWS, Azure, or GCP) and their associated ML services.
• Proficiency with containerization (Docker) and orchestration (Kubernetes).
• Experience with infrastructure as code (IaC) tools like Terraform or CloudFormation.
• Solid understanding of machine learning concepts, algorithms, and the ML lifecycle.
• Proficiency in scripting languages such as Python or Bash.
• Experience with monitoring and logging tools (e.g., Prometheus, Grafana, ELK stack).
• Excellent problem-solving, communication, and leadership skills.
• Experience in a fully remote work environment is highly desirable.

Benefits

• This fully remote position offers a highly competitive salary, attractive bonus potential, and a comprehensive suite of benefits including medical, dental, and retirement plans.
• Our client is committed to professional growth, providing access to extensive training resources, certifications, and support for attending industry-leading conferences.
• Enjoy the flexibility and work-life balance of a remote role while being an integral part of a forward-thinking AI company.
• You will work with state-of-the-art tools and technologies, contributing to impactful projects that define the future of AI operations.
• Join a collaborative and innovative team dedicated to excellence.