Senior AI/ML Operations (MLOps) Engineer

Placements24; Southampton; Hybrid; GBP 41,000 - 82,000; Full time

Benefits offered by this job

Performance-based bonus

Health insurance

Flexible work arrangements

Professional development

Job summary

Placements24 is seeking a Senior AI/ML Operations Engineer to bridge ML model development and production, building scalable MLOps pipelines and automating workflows. You will work with data scientists and engineers to deploy reliable ML solutions with CI/CD, monitoring, and security in mind.

The role requires a strong software engineering background, DevOps mindset, and deep ML lifecycle knowledge. Remote/hybrid work options and competitive compensation are offered.

Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, or related field.
• 5+ years of experience in software development, DevOps, or ML engineering.
• Proven experience implementing and managing MLOps pipelines and tools (e.g., MLflow, Kubeflow, SageMaker, Azure ML).
• Proficiency in Python.
• Experience with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes).
• Strong knowledge of CI/CD principles and tools (Jenkins, GitLab CI, GitHub Actions).
• Knowledge of ML concepts and lifecycle, monitoring and logging.

Responsibilities

• Design, implement, and manage end-to-end MLOps pipelines for machine learning models.
• Automate the build, testing, deployment, and monitoring of ML models in production.
• Collaborate with data scientists and ML engineers to streamline model development workflows.
• Manage infrastructure for ML training and inference on cloud or on-premises.
• Develop tools and scripts to improve ML operational efficiency and reliability.
• Establish monitoring and alerting for ML models to ensure performance and detect drift.
• Implement version control, testing, and CI/CD practices for ML projects.
• Ensure security, scalability, and cost-effectiveness of ML infrastructure.
• Stay up-to-date with the latest MLOps tools and practices.
• Document MLOps processes, infrastructure, and best practices.

Skills

MLOps

Python

DevOps

ML lifecycle

CI/CD

Education

Bachelor's or Master's in CS/Engineering

Tools

MLflow

Kubeflow

SageMaker

Azure ML

Docker

Kubernetes

Job description

About the Role

Our client, a dynamic tech firm at the forefront of AI innovation, is seeking a skilled Senior AI/ML Operations (MLOps) Engineer to enhance their machine learning capabilities in Randburg, Gauteng. This role is critical in bridging the gap between machine learning model development and production deployment, ensuring that our AI solutions are scalable, reliable, and efficient. You will be responsible for building and maintaining robust MLOps pipelines, automating workflows, and implementing best practices for continuous integration, delivery, and monitoring of ML models. This is an excellent opportunity to work with cutting-edge technologies, collaborate with talented data scientists and engineers, and make a significant impact on the operational excellence of our AI initiatives. We are looking for a candidate with a strong background in software engineering, DevOps principles, and a deep understanding of the machine learning lifecycle. Your expertise in Randburg will be key to streamlining our AI development and deployment processes.

Key Responsibilities

• Design, implement, and manage end-to-end MLOps pipelines for machine learning models.
• Automate the build, testing, deployment, and monitoring of ML models in production environments.
• Collaborate closely with data scientists and ML engineers to streamline model development workflows.
• Implement and manage infrastructure for ML training and inference, utilizing cloud platforms (AWS, Azure, GCP) or on-premises solutions.
• Develop tools and scripts to enhance ML operational efficiency and reliability.
• Establish monitoring and alerting systems for ML models to ensure performance and detect drift.
• Implement version control, testing, and CI/CD practices for machine learning projects.
• Ensure security, scalability, and cost-effectiveness of ML infrastructure.
• Stay up-to-date with the latest MLOps tools, technologies, and best practices.
• Document MLOps processes, infrastructure, and best practices.

Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• Minimum of 5 years of experience in software development, DevOps, or ML engineering.
• Proven experience implementing and managing MLOps pipelines and tools (e.g., MLflow, Kubeflow, SageMaker, Azure ML).
• Proficiency in scripting languages such as Python.
• Experience with cloud platforms (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes).
• Solid understanding of CI/CD principles and tools (e.g., Jenkins, GitLab CI, GitHub Actions).
• Knowledge of machine learning concepts and the ML lifecycle.
• Experience with monitoring and logging tools.
• Strong problem-solving and analytical skills.
• Excellent communication and collaboration abilities.
• Familiarity with infrastructure as code tools (e.g., Terraform, Ansible) is a plus.

Benefits

• Competitive salary and attractive performance-based bonus.
• Comprehensive health, dental, and vision insurance.
• Generous paid time off and holiday schedule.
• Professional development opportunities, including training, workshops, and conference attendance.
• Access to modern technology and collaborative tools.
• Dynamic and innovative work culture.
• Retirement savings plan with company contributions.
• Employee assistance program.
• Regular social events and team-building activities.
• Support for remote or hybrid work arrangements.