Senior Machine Learning Engineer - MLOps Specialist

Placements24; Sandton; Híbrido; ZAR 1 200 000 - 1 800 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Performance bonuses

Career advancement

Training, certifications, and конферен

Health, dental, and vision insurance

Retirement savings plan

Ample paid time off

Resumo da oferta

Placements24 in Sandton, Gauteng, is seeking a Senior Machine Learning Engineer with a strong MLOps focus. You will design and maintain scalable ML pipelines, deploy models, and ensure reliability in production within a hybrid work setup.

You will collaborate with data scientists and software engineers, implementing CI/CD, monitoring, and retraining processes. A deep understanding of ML and software engineering best practices is required.

Qualificações

• Bachelor's or Master's degree in Computer Science, Software Engineering, or related field.
• Minimum 5 years in software or ML engineering, with ≥2 years in MLOps.
• Experience building ML pipelines with Kubeflow, MLflow, or SageMaker.
• Proficient in Python and ML frameworks such as TensorFlow or PyTorch.
• Experience with cloud platforms and container orchestration (Kubernetes).

Responsabilidades

• Design, build, and maintain scalable MLOps pipelines for model training and deployment.
• Implement CI/CD practices for ML models and updates.
• Develop infrastructure for ML systems on AWS/Azure/GCP; use Docker/Kubernetes.
• Monitor drift, performance, and health; set up alerts and rollbacks.
• Collaborate with data scientists and engineers to productionize models.
• Optimize ML workflows for cost, speed, and reliability.
• Create tools to manage and operationalize ML models securely.

Conhecimentos

MLOps

Python

Cloud (AWS/Azure/GCP)

CI/CD

Git

System design

Communication

Formação académica

Bachelor's or Master's in Computer Science / Software Engineering

Ferramentas

Kubeflow

MLflow

SageMaker

Docker

Kubernetes

TensorFlow

PyTorch

Descrição da oferta de emprego

About the Role

Our client is a leader in developing intelligent automation solutions and is seeking a Senior Machine Learning Engineer with a strong MLOps specialization. This role is pivotal in building, deploying, and maintaining robust and scalable machine learning systems. You will be responsible for streamlining the entire ML lifecycle, from data preparation and model training to deployment, monitoring, and retraining. This position requires a deep understanding of both machine learning principles and software engineering best practices, with a focus on operationalizing AI. Located in the bustling hub of Sandton, Gauteng , this role offers a hybrid work arrangement, blending focused remote work with collaborative in-office sessions. You will contribute to high-impact projects in a fast-paced, innovative environment.

Key Responsibilities

• Design, build, and maintain scalable and reliable MLOps pipelines for automated model training, validation, and deployment.
• Implement CI/CD practices for machine learning models, ensuring smooth and efficient model updates.
• Develop and manage infrastructure for machine learning systems, leveraging cloud platforms (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes).
• Monitor the performance, drift, and health of deployed machine learning models, establishing alerting and rollback mechanisms.
• Collaborate with data scientists and software engineers to ensure models are production-ready and integrated seamlessly into applications.
• Optimize ML workflows for efficiency, cost-effectiveness, and speed.
• Develop tools and frameworks to facilitate the management and operationalization of machine learning models.
• Ensure adherence to security best practices and compliance requirements for ML systems.

Requirements

• Bachelor's or Master's degree in Computer Science, Software Engineering, or a related quantitative field.
• Minimum of 5 years of experience in software engineering or machine learning engineering, with at least 2 years focused on MLOps.
• Proven experience in building and managing ML pipelines using tools like Kubeflow, MLflow, SageMaker, or similar platforms.
• Strong proficiency in Python and experience with ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
• Hands-on experience with cloud computing platforms (AWS, Azure, GCP) and container orchestration (Kubernetes).
• Solid understanding of software development best practices, including version control (Git) and CI/CD.
• Excellent problem-solving, debugging, and system design skills.
• Strong communication and collaboration abilities, especially in a hybrid work setting.

Benefits

Our client offers a highly competitive salary and a comprehensive benefits package, including performance bonuses and opportunities for career advancement. We provide generous support for professional development, including training, certifications, and conference attendance. Employees benefit from excellent health, dental, and vision insurance, a robust retirement savings plan, and ample paid time off. The hybrid work model in Sandton, Gauteng , fosters a healthy work-life balance, encouraging both focused individual work and productive team collaboration. Join us to shape the future of operationalizing AI.