Remote Lead Machine Learning Engineer

Placements24; Randburg; Hybrid; ZAR 1,990,000 - 2,985,000; Full time

Benefits offered by this job

Remote-first culture

Health insurance

Flexible PTO

Retirement plan options

Job summary

Placements24 is seeking a Remote Lead Machine Learning Engineer to spearhead the development and deployment of production-grade ML systems. You will design scalable pipelines, mentor a team, and drive ML infrastructure across the stack in a remote-first environment.

You will collaborate with data scientists, software engineers, and product managers to translate business needs into technical solutions, while staying ahead of industry trends and ensuring scalable, reliable solutions in a remote

Qualifications

• Master's or PhD in Computer Science, Engineering, Statistics, or related field.
• 7+ years of ML engineering experience, with a focus on production systems.
• Proven experience leading engineering teams.
• Expertise in Python and ML libraries (scikit-learn, TensorFlow, PyTorch).
• Strong MLOps experience with MLflow, Kubeflow, Docker and Kubernetes.
• Proficiency with cloud platforms (AWS/Azure/GCP) and their ML services.
• Solid understanding of data engineering, distributed systems, and software dev best practices.
• Excellent problem-solving and collaboration in remote teams.
• Experience with large-scale data processing (e.g., Spark) is a plus.

Responsibilities

• Lead design, development, and deployment of production-grade ML systems and infrastructure.
• Architect scalable ML pipelines for data processing, model training, evaluation, and deployment (MLOps).
• Collaborate with data scientists, software engineers, and product managers to translate requirements into technical solutions.
• Mentor and guide ML engineers, promoting technical excellence and best practices.
• Ensure performance, scalability, reliability, and maintainability of deployed ML models.
• Implement and manage tools for ML development, monitoring, and versioning.
• Stay current with industry trends, emerging technologies, and MLOps best practices.
• Contribute to strategic decisions on ML tech stack and architecture.
• Troubleshoot complex issues in ML systems and production environments.
• Drive continuous improvement in ML development processes and operational efficiency.

Skills

Team leadership

Python

scikit-learn

TensorFlow

PyTorch

MLOps

Cloud platforms

Distributed systems

Data engineering

Remote collaboration

Education

Master's or PhD in CS/Engineering/Statistics

Tools

MLflow

Kubeflow

Docker

Kubernetes

Spark

AWS

Job description

About the Role

Our client, a global leader in data analytics and AI solutions, is seeking a Remote Lead Machine Learning Engineer to spearhead the development and deployment of advanced machine learning systems. This fully remote position allows you to work from anywhere, contributing to impactful projects with a world-class team. The Lead ML Engineer will be responsible for designing robust ML pipelines, overseeing model development and productionisation, and mentoring a talented team of engineers. You will play a critical role in driving innovation and ensuring the scalability and reliability of our client's ML infrastructure. This is an exceptional opportunity to shape the future of machine learning applications in a flexible, remote-first environment. We are looking for a strategic thinker and technical leader with a passion for building high-quality ML solutions.

Key Responsibilities

• Lead the design, development, and deployment of production-grade machine learning systems and infrastructure.
• Architect scalable and efficient ML pipelines for data processing, model training, evaluation, and deployment (MLOps).
• Collaborate with data scientists, software engineers, and product managers to translate business requirements into technical solutions.
• Mentor and guide a team of machine learning engineers, fostering technical excellence and best practices.
• Ensure the performance, scalability, reliability, and maintainability of deployed ML models.
• Implement and manage tools and frameworks for ML development, monitoring, and versioning.
• Stay current with industry trends, emerging technologies, and best practices in machine learning and MLOps.
• Contribute to strategic decision-making regarding ML technology stack and architecture.
• Troubleshoot and resolve complex issues in ML systems and production environments.
• Drive continuous improvement in ML development processes and operational efficiency.

Requirements

• Master's or PhD in Computer Science, Engineering, Statistics, or a related quantitative field.
• 7+ years of experience in machine learning engineering, with a significant focus on production systems.
• Proven experience leading engineering teams and mentoring junior engineers.
• Expertise in Python and common ML libraries (e.g., scikit-learn, TensorFlow, PyTorch).
• Strong experience with MLOps principles and tools (e.g., MLflow, Kubeflow, Docker, Kubernetes).
• Proficiency in cloud platforms such as AWS, Azure, or GCP, and their ML services.
• Solid understanding of data engineering, distributed systems, and software development best practices.
• Excellent problem-solving, analytical, and debugging skills.
• Strong communication and collaboration skills, adept at working in a remote team environment.
• Experience with large-scale data processing frameworks (e.g., Spark) is a plus.

Benefits

• Our client offers a highly competitive salary and a comprehensive remote work benefits package, including excellent health insurance, flexible paid time off, and retirement plan options.
• This role provides the ultimate flexibility of working from home, coupled with the opportunity to work on challenging and impactful projects with a global impact.
• We offer continuous learning opportunities, including support for conferences and advanced training.
• Join a collaborative and innovative remote-first culture where your contributions are valued and you can truly shape the direction of machine learning.