Senior AI Engineer - Deep Learning Platforms

Placements24; Benoni; On-site; ZAR 1,000,000 - 1,500,000; Full time

Benefits offered by this job

Bonuses

Health insurance

Paid time off

Training opportunities

Stock options

Remote work support

Job summary

Placements24 is seeking a Senior AI Engineer with deep learning platform expertise to join our Benoni-based research and development team. You will design scalable DL pipelines, optimize distributed training, and manage ML workloads across cloud or on-prem environments.

You will work closely with AI researchers to productionize models, implement MLOps practices, and contribute to a state-of-the-art AI stack using TensorFlow, PyTorch, or Keras.

Qualifications

• Master's or Ph.D. in Computer Science, Machine Learning, or a related field.
• Minimum of 5 years of experience in software or ML engineering with a focus on deep learning platforms.
• Proficiency in Python and deep learning frameworks such as TensorFlow, PyTorch, or Keras.

Responsibilities

• Design, implement, and maintain scalable deep learning pipelines and infrastructure.
• Develop and optimize distributed training systems for large-scale neural networks.
• Manage ML workloads on cloud platforms (AWS, Azure, GCP) or on-premises clusters.
• Implement and refine MLOps practices for model deployment, monitoring, and management.
• Collaborate with researchers and data scientists to integrate models into production systems.

Skills

Python

Deep learning

Distributed training

MLOps

TensorFlow

PyTorch

Keras

Education

Master's or Ph.D. in Computer Science, ML, or related field

Tools

Docker

Kubernetes

MLflow

Kubeflow

Spark

CI/CD

Job description

About the Role

Our client, a leading innovator in artificial intelligence solutions, is looking for a Senior AI Engineer with specialized expertise in Deep Learning Platforms to join their cutting-edge research and development team in **Benoni, Gauteng**. This role is central to building, scaling, and optimizing the infrastructure that powers our advanced deep learning models. You will be responsible for developing robust ML pipelines, managing distributed training environments, and ensuring the efficient deployment of AI models into production. This is an exceptional opportunity to work with state-of-the-art technology, collaborate with world-class AI researchers, and contribute to projects that are shaping the future of AI. We seek a candidate with strong software engineering skills, deep knowledge of deep learning frameworks, and hands-on experience with cloud platforms. Your contributions in **Benoni** will directly impact the performance and scalability of our AI innovations. This position offers a dynamic environment where technical challenges are met with creative solutions and continuous learning is encouraged.

Key Responsibilities

• Design, implement, and maintain scalable deep learning pipelines and infrastructure.
• Develop and optimize distributed training systems for large-scale neural networks.
• Manage and orchestrate ML workloads on cloud platforms (AWS, Azure, GCP) or on-premises clusters.
• Implement and refine MLOps practices for efficient model deployment, monitoring, and management.
• Collaborate with AI researchers and data scientists to integrate new models and algorithms into production systems.
• Develop tools and frameworks to improve the efficiency and productivity of AI development teams.
• Ensure the reliability, performance, and scalability of AI/ML infrastructure.
• Troubleshoot and resolve issues related to deep learning systems and infrastructure.
• Stay current with advancements in deep learning frameworks, MLOps tools, and cloud technologies.
• Contribute to the documentation and best practices for AI platform development.

Requirements

• Master's or Ph.D. degree in Computer Science, Machine Learning, or a related field.
• Minimum of 5 years of experience in software engineering or ML engineering, with a strong focus on deep learning platforms.
• Proficiency in Python and experience with deep learning frameworks such as TensorFlow, PyTorch, or Keras.
• Hands-on experience with cloud platforms (AWS, Azure, GCP) and their AI/ML services.
• Experience with containerization technologies like Docker and orchestration tools like Kubernetes.
• Solid understanding of MLOps principles and tools (e.g., MLflow, Kubeflow).
• Experience with distributed computing frameworks (e.g., Spark) and data processing pipelines.
• Strong software engineering best practices, including version control (Git) and CI/CD.
• Excellent problem-solving and debugging skills.
• Strong communication and teamwork abilities.

Benefits

• Competitive salary and performance-based bonuses.
• Comprehensive health, dental, and vision insurance.
• Generous paid time off and company holidays.
• Opportunities for professional growth and development, including access to training and conferences.
• State-of-the-art technology stack and research environment.
• Collaborative team culture focused on innovation.
• Retirement savings plan with employer matching.
• Potential for stock options or equity participation.
• Regular team-building events.
• On-site amenities (if applicable) or remote work support.