Lead Machine Learning Engineer - Cloud Platforms

Placements24; Kempton Park; Remote; ZAR 1,400,000 - 2,400,000; Full time

Benefits offered by this job

Remote-first culture

Professional development budget

Equipment stipend

Flexible time off

Job summary

Placements24 is seeking a Lead Machine Learning Engineer to spearhead the design, development, and deployment of production ML systems in a remote-first setup. You will architect scalable pipelines across cloud platforms and mentor a global team of engineers, translating research into robust, production-ready solutions.

The role requires a strong background in ML engineering, deep knowledge of MLOps, and proven leadership skills to drive strategic AI initiatives while collaborating with data

Qualifications

• Master's or PhD in CS/Engineering with ML specialization.
• 7+ years in ML engineering; 3+ years in lead role.
• Extensive production ML model deployment in cloud.
• Strong Python skills; TF, PyTorch, or scikit-learn.
• Experience with cloud ML services (SageMaker, Azure ML, Vertex AI).
• Deep knowledge of MLOps (Kubeflow, MLflow, Docker, Kubernetes).
• Proven remote-team leadership and collaboration.

Responsibilities

• Lead end-to-end ML systems design, development, and deployment.
• Architect scalable ML pipelines on AWS/Azure/GCP.
• Tune and deploy models for performance and efficiency.
• Collaborate with data scientists and software engineers.
• Enforce MLOps practices: CI/CD, monitoring, logging, versioning.
• Mentor a remote team of ML engineers.
• Evaluate new technologies to boost ML capabilities.
• Troubleshoot production ML issues.
• Contribute to AI strategy and roadmap.

Skills

Leadership

ML Engineer

Python

TensorFlow

PyTorch

Cloud Platforms

MLOps

Kubernetes

Education

Master's or PhD in CS or related

Tools

Kubeflow

MLflow

Docker

Kubernetes

SageMaker

Vertex AI

Job description

About the Role

Our client is a pioneering force in cloud-based AI solutions, seeking an exceptional Lead Machine Learning Engineer to spearhead their efforts in developing and deploying scalable ML systems. This is a fully remote, critical role based out of our virtual operations hub, allowing you to contribute your expertise from anywhere. You will be at the forefront of architecting robust machine learning pipelines, optimizing model performance, and ensuring the reliability of our AI services. This position demands a blend of deep technical expertise in ML engineering and strong leadership capabilities. You will guide a talented team of engineers, foster innovation, and drive the strategic direction of our machine learning initiatives, all within a dynamic and forward-thinking organization that embraces a remote-first culture.

Key Responsibilities

• Lead the design, development, and deployment of end-to-end machine learning systems and infrastructure.
• Architect and implement scalable, production-ready ML pipelines using cloud technologies (AWS, Azure, GCP).
• Oversee the selection, tuning, and deployment of various machine learning models, ensuring optimal performance and efficiency.
• Collaborate closely with data scientists and software engineers to translate research into deployable products.
• Establish and enforce best practices for MLOps, including CI/CD, monitoring, logging, and version control for ML models and data.
• Mentor and guide a team of machine learning engineers, fostering a collaborative and high-performance remote work environment.
• Identify and evaluate new technologies and methodologies to enhance our ML capabilities.
• Troubleshoot and resolve complex issues in production ML systems.
• Contribute to strategic planning and roadmap development for AI and ML initiatives.

Requirements

• Master's or Ph.D. in Computer Science, Engineering, or a related field, with a specialization in Machine Learning or a related area.
• Minimum of 7 years of experience in machine learning engineering, with at least 3 years in a lead or senior role.
• Extensive experience building and deploying ML models in production environments, preferably in a cloud setting.
• Strong proficiency in Python and ML frameworks such as TensorFlow, PyTorch, or scikit-learn.
• Hands-on experience with cloud platforms (AWS, Azure, GCP) and their ML services (e.g., SageMaker, Azure ML, Vertex AI).
• Solid understanding of MLOps principles and tools (e.g., Kubeflow, MLflow, Docker, Kubernetes).
• Demonstrated ability to lead and mentor engineering teams, with excellent communication and collaboration skills suitable for remote work.
• Experience with big data technologies (e.g., Spark, Hadoop) is a plus.
• A strong commitment to remote work best practices and a proactive approach to communication.

Benefits

• As a fully remote position, this role offers unparalleled flexibility.
• Our client provides a highly competitive salary, comprehensive health and wellness benefits, generous paid time off, and a dedicated budget for professional development, including online courses, conferences, and certifications.
• You’ll have the opportunity to work with a talented, diverse, and globally distributed team, contributing to impactful AI projects.
• We also offer equipment stipends and support for creating an optimal home office setup.
• This is a unique chance to advance your career in a leading-edge field while enjoying the freedom and autonomy of a remote-first workplace, enabling you to collaborate effectively from Tembisa, Gauteng, or any location worldwide.