Lead Machine Learning Engineer - Cloud AI Platforms

Placements24; Cape Town; Hybrid; ZAR 2,326,000 - 3,822,000; Full time

Benefits offered by this job

Fully remote work setup

Stock option plan

Learning & development opportunities

Job summary

Our client, a globally recognized leader in cloud computing and AI, seeks a seasoned Lead Machine Learning Engineer to drive the next generation of cloud AI platforms. This remote role offers the chance to influence infrastructure that serves millions of users, with a strong emphasis on scalable ML systems and production-ready services.

You will lead design, development and deployment across AWS/Azure/GCP, build MLOps pipelines, and mentor a team of ML engineers while collaborating closely with

Qualifications

• Master's or PhD in Computer Science, Engineering or related field, or equivalent practical experience.
• 8+ years of software engineering experience with a strong ML focus.
• Experience designing, building, and deploying ML models and platforms in cloud environments (AWS/Azure/GCP).
• Deep understanding of ML algorithms, statistics, and data structures.
• Proficiency in Python, Java or C++, with ML libraries (TensorFlow, PyTorch, scikit-learn).
• Strong MLOps experience with Docker, Kubernetes, MLflow, Kubeflow.
• Excellent leadership, communication and collaboration skills.
• Experience with distributed computing frameworks (e.g., Spark) a plus.
• Ability to work independently in a fully remote setting.

Responsibilities

• Lead design, development, and deployment of large-scale ML systems on cloud infrastructure (AWS/Azure/GCP).
• Architect and implement MLOps pipelines for training, deployment, monitoring and management.
• Develop and optimize distributed training frameworks and inference engines.
• Collaborate with product managers and researchers to translate models into production services.
• Mentor and guide ML engineers, fostering technical excellence and innovation.
• Ensure scalability, reliability and performance of cloud AI platforms.
• Contribute to selection and integration of ML technologies and tools.
• Troubleshoot complex production ML issues.

Skills

ML systems design

Cloud platforms (AWS/Azure/GCP)

MLOps

Distributed training

Programming (Python/Java/C++)

Team leadership

Remote work

Education

Masters/PhD in CS/Engineering

Tools

Docker

Kubernetes

MLflow

Kubeflow

TensorFlow

PyTorch

Spark

Job description

About the Role

Our client is a globally recognized leader in cloud computing and AI innovation, seeking a seasoned Lead Machine Learning Engineer to spearhead the development of their next-generation cloud AI platforms. This is a fully remote role, allowing you to contribute from anywhere while being an integral part of our highly collaborative and distributed team. You will be responsible for designing, building, and deploying scalable machine learning systems that power a wide array of intelligent services. This is a unique chance to influence the direction of cloud-based AI infrastructure and to work on complex challenges with a profound impact on millions of users. The ideal candidate will possess a strong blend of software engineering rigor and deep machine learning expertise, with a passion for building robust and efficient AI solutions.

Key Responsibilities

• Lead the design, development, and deployment of large-scale machine learning systems on cloud infrastructure (AWS, Azure, GCP).
• Architect and implement MLOps pipelines for model training, deployment, monitoring, and management.
• Develop and optimize distributed training frameworks and inference engines.
• Collaborate with product managers and research scientists to define requirements and translate cutting-edge ML models into production-ready services.
• Mentor and guide a team of talented ML engineers, fostering a culture of technical excellence and innovation.
• Ensure the scalability, reliability, and performance of cloud AI platforms.
• Contribute to the selection and integration of appropriate ML technologies and tools.
• Troubleshoot and resolve complex technical issues in production ML environments.

Requirements

• Master's or PhD degree in Computer Science, Engineering, or a related quantitative field, or equivalent practical experience.
• Extensive experience (8+ years) in software engineering, with a significant focus on machine learning systems.
• Proven experience in designing, building, and deploying ML models and platforms in a cloud environment (AWS, Azure, or GCP).
• Deep understanding of ML algorithms, statistical modeling, and data structures.
• Proficiency in programming languages such as Python, Java, or C++, and experience with ML libraries (e.g., TensorFlow, PyTorch, scikit-learn).
• Strong experience with MLOps practices and tools (e.g., Docker, Kubernetes, MLflow, Kubeflow).
• Excellent leadership, communication, and interpersonal skills.
• Experience with distributed computing frameworks (e.g., Spark) is a plus.
• Ability to work independently and effectively in a fully remote setting.

Benefits

• As a fully remote position, our client offers unparalleled flexibility and work-life balance.
• We provide a highly competitive salary, comprehensive health and wellness benefits, and a generous stock option plan.
• Continuous learning is encouraged through access to online courses, industry conferences, and internal knowledge-sharing sessions.
• You will have the opportunity to work on impactful projects with a global team of experts, shaping the future of AI.
• Our client invests in your growth, offering clear career progression paths and opportunities to lead significant initiatives.
• This role is perfect for an experienced ML leader seeking a challenging and rewarding remote-first career.