Lead Machine Learning Engineer (Remote)

Placements24; Gauteng; Hybrid; ZAR 1,200,000 - 1,700,000; Full time

Benefits offered by this job

Fully remote work

Professional development budget

Stock options

Health insurance

Job summary

Placements24 is seeking a Lead Machine Learning Engineer to architect scalable ML systems and guide a remote team of engineers in deploying production-grade pipelines. The role demands mentoring, collaboration with data scientists and product managers, and driving innovations in ML at scale.

The ideal candidate has a PhD or MSc, 5+ years of ML and software development, and deep expertise in Python and ML frameworks. Remote work is fully supported with a strong emphasis on results.

Qualifications

• Master's or PhD in Computer Science, Engineering, or a related quantitative field.
• 5+ years hands-on experience in machine learning engineering and software development.
• Proven experience leading technical teams and managing ML projects.
• Proficiency in Python and common ML libraries/frameworks (TensorFlow, PyTorch).
• Strong understanding of MLOps principles, CI/CD, and cloud platforms (AWS, Azure, GCP).
• Excellent problem-solving skills and the ability to thrive in a remote, collaborative environment.

Responsibilities

• Lead the design and architecture of scalable machine learning systems and MLOps pipelines.
• Develop, train, and deploy machine learning models for various applications, optimizing for performance and efficiency.
• Mentor and guide a team of ML engineers, fostering best practices in software development and ML engineering.
• Collaborate with data scientists and product managers to translate business requirements into technical solutions.
• Implement robust monitoring, logging, and alerting systems for ML models in production.
• Stay current with advancements in ML technologies and contribute to the company's AI strategy.

Skills

Team leadership

Remote collaboration

Strategic thinking

Education

Master's or PhD in CS/Engineering

Tools

Python

TensorFlow

PyTorch

Scikit-learn

CI/CD

AWS/Azure/GCP

Job description

About the Role

Our client is seeking an experienced and visionary Lead Machine Learning Engineer to spearhead their AI initiatives in a fully remote capacity. This senior role involves leading a team of talented engineers in the design, development, and deployment of scalable machine learning solutions that drive significant business value. You will be responsible for architectural decisions, mentoring team members, and ensuring the successful implementation of complex ML pipelines. This is a key position for someone passionate about building robust, production-grade ML systems and driving innovation from a distance, contributing to a highly collaborative and results-oriented remote engineering culture.

Key Responsibilities

• Lead the design and architecture of scalable machine learning systems and MLOps pipelines.
• Develop, train, and deploy machine learning models for various applications, optimizing for performance and efficiency.
• Mentor and guide a team of ML engineers, fostering best practices in software development and ML engineering.
• Collaborate with data scientists and product managers to translate business requirements into technical solutions.
• Implement robust monitoring, logging, and alerting systems for ML models in production.
• Stay current with advancements in ML technologies and contribute to the company's AI strategy.

Requirements

• Master's or Ph.D. in Computer Science, Engineering, or a related quantitative field.
• 5+ years of hands‑on experience in machine learning engineering and software development.
• Proven experience leading technical teams and managing ML projects.
• Expertise in Python and common ML libraries/frameworks (e.g., Scikit-learn, TensorFlow, PyTorch).
• Strong understanding of MLOps principles, CI/CD, and cloud platforms (AWS, Azure, GCP).
• Excellent problem-solving skills and the ability to thrive in a remote, collaborative environment.

Benefits

• Highly competitive salary and potential for stock options.
• Fully remote work arrangement with flexible hours.
• Generous professional development budget and opportunities for continuous learning.
• Comprehensive health, dental, and vision insurance.
• Opportunity to lead impactful projects and shape the future of AI at our client.