Senior Machine Learning Engineer

Placements24; Soweto; Hybrid; ZAR 1,200,000 - 2,000,000; Full time

Benefits offered by this job

Bonuses

Health insurance

PTO & flexible hours

Virtual conferences

Remote work setup

Job summary

Placements24 is seeking a Senior Machine Learning Engineer to join a remote-first team. You will design, build, and deploy scalable ML models and systems, guiding data-driven initiatives across the platform.

The role requires a strong Python background, experience with TensorFlow/PyTorch, and cloud/container know-how to deliver production-ready solutions in a distributed environment.

Qualifications

• Master's or Ph.D. in Computer Science, Machine Learning, Statistics, or a related quantitative field.
• Minimum of 6 years of experience in machine learning engineering or a closely related role.
• Strong proficiency in programming languages such as Python, and ML libraries like TensorFlow, PyTorch, scikit-learn.
• Experience with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes).
• Solid understanding of data structures, algorithms, and software engineering best practices.
• Proven ability to work effectively in a remote , collaborative team setting.

Responsibilities

• Design, develop, and implement robust machine learning models and algorithms for various applications.
• Build and maintain scalable ML infrastructure, pipelines, and deployment systems.
• Collaborate with data scientists, software engineers, and product managers to integrate ML solutions into production.
• Perform data preprocessing, feature engineering, and model validation to ensure performance and accuracy.
• Optimize ML models for performance, efficiency, and scalability in cloud environments.
• Stay current with the latest advancements in ML research and apply them to practical challenges.

Skills

Python

TensorFlow

PyTorch

scikit-learn

Remote collaboration

Education

Master's degree in Computer Science / ML / Statistics

PhD in a related quantitative field

Tools

Docker

Kubernetes

AWS

Azure

GCP

Job description

About the Role

Our client is looking for an experienced Senior Machine Learning Engineer to join their innovative, remote-first team. This role is crucial for designing, building, and deploying scalable machine learning models and systems that drive key business initiatives. You will work on cutting-edge AI/ML projects, from conceptualization and data preprocessing to model training, evaluation, and production deployment. The ideal candidate is passionate about leveraging data to solve complex problems, possesses strong programming skills, and thrives in a collaborative, distributed environment. This is a fantastic opportunity to make a significant impact on a growing platform with the flexibility of remote work.

Key Responsibilities

• Design, develop, and implement robust machine learning models and algorithms for various applications.
• Build and maintain scalable ML infrastructure, pipelines, and deployment systems.
• Collaborate with data scientists, software engineers, and product managers to integrate ML solutions into production.
• Perform data preprocessing, feature engineering, and model validation to ensure performance and accuracy.
• Optimize ML models for performance, efficiency, and scalability in cloud environments.
• Stay current with the latest advancements in ML research and apply them to practical challenges.

Requirements

• Master's or Ph.D. in Computer Science, Machine Learning, Statistics, or a related quantitative field.
• Minimum of 6 years of experience in machine learning engineering or a closely related role.
• Strong proficiency in programming languages such as Python, and ML libraries like TensorFlow, PyTorch, scikit-learn.
• Experience with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes).
• Solid understanding of data structures, algorithms, and software engineering best practices.
• Proven ability to work effectively in a remote , collaborative team setting.

Benefits

• Highly competitive salary and performance-based bonuses.
• Comprehensive health, dental, and vision insurance.
• Generous paid time off and flexible working hours.
• Opportunities for professional development, training, and attending virtual conferences.
• Fully remote work setup, allowing for flexibility and work-life balance from anywhere.