Remote Lead ML Engineer: Scalable AI & MLOps Leader

Placements24; Cape Town; Hybrid; ZAR 2,241,000 - 3,201,000; Full time

Benefits offered by this job

Fully remote work

Bonus structure

Health, dental, vision insurance

Stock options

Growth opportunities

Job summary

Placements24 seeks a Lead Machine Learning Engineer to spearhead advanced AI initiatives in a fully remote role serving the Cape Town tech community. You will architect scalable ML systems, guide a team of engineers, and drive MLOps best practices from home.

You will mentor engineers, design end-to-end ML pipelines, and collaborate with data scientists and product managers to translate complex business challenges into AI solutions with impact.

Qualifications

• Master's or PhD in Computer Science, Engineering, or a related field.
• 7+ years in machine learning engineering with at least 2 years in a lead or senior role.
• Proven track record designing and deploying large-scale ML systems in production.
• Experience with Python and cloud platforms (AWS, Azure, GCP).
• Strong knowledge of MLOps tools and practices (Docker, Kubernetes, CI/CD).

Responsibilities

• Lead the design, development, and deployment of end-to-end ML pipelines and infrastructure.
• Mentor and manage a team of ML engineers, providing technical guidance.
• Develop and implement robust MLOps practices for model training, deployment, monitoring, and versioning.
• Collaborate with data scientists and product managers to define ML project requirements and roadmaps.
• Ensure the scalability, reliability, and efficiency of production ML systems.
• Drive research and adoption of new ML technologies and methodologies.

Skills

Python

MLOps

Docker

Kubernetes

CI/CD

AWS

Azure

GCP

Leadership

Education

Master's or PhD in CS/Engineering

Tools

CI/CD tooling

Job description

Placements24 seeks a Lead Machine Learning Engineer to spearhead advanced AI initiatives in a fully remote role serving the Cape Town tech community. You will architect scalable ML systems, guide a team of engineers, and drive MLOps best practices from home.

You will mentor engineers, design end-to-end ML pipelines, and collaborate with data scientists and product managers to translate complex business challenges into AI solutions with impact.