Remote Lead ML Engineer: Scalable AI & MLOps Leader

Placements24

Cape Town

Hybrid

ZAR 2,241,000 - 3,201,000

Full time

7 days ago
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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.

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