Senior AI Engineer - Deep Learning Infrastructure

Placements24; LegKraal Gate; Hybrid; ZAR 900,000 - 1,500,000; Full time

Benefits offered by this job

Health insurance

Retirement plans

Stock options

Remote work flexibility

Job summary

Placements24 is seeking a highly experienced Senior AI Engineer to join a fully remote engineering team focused on building scalable AI infrastructure for large-scale model development and deployment. You will design and optimize cloud-based systems across AWS, GCP, and Azure, collaborating with researchers to deliver robust ML platforms.

The role emphasizes distributed training pipelines, MLOps workflows, and security/compliance, with mentorship for junior engineers and a strong remote-work

Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, or a related quantitative field.
• Minimum of 5 years of experience in software engineering, with at least 3 years focused on AI/ML infrastructure or MLOps.
• Proficiency in programming languages such as Python, Go, or Java.
• Extensive experience with cloud computing platforms (AWS, GCP, or Azure) and their associated services.
• Strong understanding of containerization technologies (Docker, Kubernetes).
• Hands-on experience with deep learning frameworks (e.g., TensorFlow, PyTorch, Keras).
• Experience with distributed systems and parallel computing concepts.
• Familiarity with MLOps tools and best practices (e.g., MLflow, Kubeflow, CI/CD pipelines).
• Excellent problem-solving, debugging, and performance optimization skills.
• Strong communication and collaboration skills, crucial for a remote team.

Responsibilities

• Design, implement, and maintain scalable and efficient deep learning infrastructure on cloud platforms (AWS, GCP, Azure).
• Develop and optimize distributed training pipelines for complex deep learning models.
• Build and manage MLOps workflows, including CI/CD, model versioning, and deployment automation.
• Collaborate with AI researchers and data scientists to understand their infrastructure needs and provide robust solutions.
• Implement monitoring, logging, and alerting systems for AI infrastructure components.
• Troubleshoot and resolve issues related to performance, scalability, and reliability of AI systems.
• Stay up-to-date with the latest advancements in AI infrastructure, distributed systems, and deep learning technologies.
• Contribute to the development of internal tools and frameworks to improve AI development efficiency.
• Ensure the security and compliance of AI infrastructure.
• Mentor junior engineers and promote best practices in AI engineering.

Skills

Python

Go

Java

Cloud platforms (AWS/GCP/Azure)

Docker

Kubernetes

TensorFlow

PyTorch

MLOps

CI/CD

Education

Bachelor's or Master's in CS/Engineering

Tools

MLflow

Kubeflow

CI/CD tooling

Job description

About the Role

Our client, a leader in AI-driven solutions, is seeking a highly experienced Senior AI Engineer to join their fully remote engineering team. This critical role focuses on designing, building, and optimizing the infrastructure required to support large-scale deep learning model development and deployment. You will be instrumental in ensuring the scalability, reliability, and efficiency of our AI platforms, working with cutting-edge technologies. The ideal candidate possesses a strong background in software engineering, cloud computing, and deep learning frameworks, with a proven track record of building robust AI systems. Join us in pushing the boundaries of AI from your remote workspace, contributing to innovative projects relevant to Mahikeng, North West, ZA .

Key Responsibilities

• Design, implement, and maintain scalable and efficient deep learning infrastructure on cloud platforms (AWS, GCP, Azure).
• Develop and optimize distributed training pipelines for complex deep learning models.
• Build and manage MLOps workflows, including CI/CD, model versioning, and deployment automation.
• Collaborate with AI researchers and data scientists to understand their infrastructure needs and provide robust solutions.
• Implement monitoring, logging, and alerting systems for AI infrastructure components.
• Troubleshoot and resolve issues related to performance, scalability, and reliability of AI systems.
• Stay up-to-date with the latest advancements in AI infrastructure, distributed systems, and deep learning technologies.
• Contribute to the development of internal tools and frameworks to improve AI development efficiency.
• Ensure the security and compliance of AI infrastructure.
• Mentor junior engineers and promote best practices in AI engineering.

Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, or a related quantitative field.
• Minimum of 5 years of experience in software engineering, with at least 3 years focused on AI/ML infrastructure or MLOps.
• Proficiency in programming languages such as Python, Go, or Java.
• Extensive experience with cloud computing platforms (AWS, GCP, or Azure) and their associated services.
• Strong understanding of containerization technologies (Docker, Kubernetes).
• Hands-on experience with deep learning frameworks (e.g., TensorFlow, PyTorch, Keras).
• Experience with distributed systems and parallel computing concepts.
• Familiarity with MLOps tools and best practices (e.g., MLflow, Kubeflow, CI/CD pipelines).
• Excellent problem-solving, debugging, and performance optimization skills.
• Strong communication and collaboration skills, crucial for a remote team.

Benefits

Our client offers a highly competitive salary, a comprehensive benefits package including health insurance and retirement plans, and significant opportunities for professional growth and learning. As a fully remote position, we provide exceptional flexibility and promote a healthy work-life balance. Employees will have access to state-of-the-art tools and technologies, and the chance to work on challenging and impactful AI projects. Performance bonuses and stock options are part of our attractive compensation structure. This role offers the unique opportunity to be at the forefront of AI development without geographical limitations.