Senior Machine Learning Engineer

Placements24; Paarl; Hybrid; ZAR 900,000 - 1,500,000; Full time

Benefits offered by this job

Competitive salary

Insurance (medical, dental, vision)

Stock options

Learning opportunities

Remote-friendly culture

State-of-the-art tech

Job summary

Placements24 is seeking an experienced Senior Machine Learning Engineer in Paarl to lead the development and deployment of advanced ML systems. You will architect, build, and scale ML pipelines, optimize models for production, and collaborate with data scientists and software engineers.

This role offers opportunities to work on recommendation engines, fraud detection, and forecasting within a supportive, innovative environment, with remote-friendly policies and access to state-of-the-art tools.

Qualifications

• Bachelor's or Master's in CS, Engineering, or quantitative field.
• 5+ years of professional software engineering with ML.
• Proficiency in Python and ML libraries (TensorFlow, PyTorch, Scikit-learn).
• Experience with cloud platforms and containers; MLOps tooling.

Responsibilities

• Design, implement, and maintain scalable ML pipelines from data ingestion to deployment.
• Optimize ML models for performance, accuracy, and efficiency in production environments.
• Collaborate with data scientists to deploy research models into robust, production-ready systems.
• Develop and implement MLOps practices for CI/CD, delivery, and monitoring of ML models.
• Troubleshoot and resolve issues related to ML model performance and infrastructure.
• Mentor junior engineers and contribute to the team's technical growth.

Skills

Python

Machine Learning

Problem solving

Collaboration

Education

Bachelor's or Master's in CS/Engineering

Tools

TensorFlow

PyTorch

Scikit-learn

AWS

Azure

GCP

Docker

Job description

About the Role

Our client is looking for an experienced Senior Machine Learning Engineer to lead the development and deployment of advanced ML systems in Paarl . This role involves architecting, building, and scaling ML pipelines, optimizing models for production, and collaborating closely with data scientists and software engineers. You will tackle complex challenges in areas like recommendation engines, fraud detection, and forecasting, ensuring that our ML solutions are robust, efficient, and impactful. This is an excellent opportunity for a seasoned engineer to make significant contributions to cutting-edge AI projects within a supportive and innovative environment, driving the technical direction of ML initiatives.

Key Responsibilities

• Design, implement, and maintain scalable machine learning pipelines from data ingestion to model deployment.
• Optimize ML models for performance, accuracy, and efficiency in production environments.
• Collaborate with data scientists to deploy research models into robust, production-ready systems.
• Develop and implement MLOps best practices for continuous integration, delivery, and monitoring of ML models.
• Troubleshoot and resolve issues related to ML model performance and infrastructure.
• Mentor junior engineers and contribute to the team's technical growth and knowledge sharing.

Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, or a related quantitative field.
• 5+ years of professional experience in software engineering with a strong focus on machine learning.
• Proficiency in programming languages such as Python, and expertise with ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
• Hands-on experience with cloud platforms (AWS, Azure, GCP) and containerization technologies.
• Experience with MLOps tools and workflows for managing the ML lifecycle.
• Strong problem-solving abilities and a proactive approach to tackling complex engineering challenges in Paarl .

Benefits

• Highly competitive salary and performance-based incentives.
• Comprehensive medical, dental, and vision insurance.
• Stock options and long-term incentive programs.
• Opportunities for continuous learning, training, and conference attendance.
• A flexible, remote-friendly work culture to support team members in Paarl .
• Access to state-of-the-art technology and development tools.