Machine Learning Engineer

Placements24; East London; Hybrid; ZAR 1,983,000 - 2,975,000; Full time

Benefits offered by this job

Performance bonuses

Global health, dental, and vision

Professional development allowance

Stock options

Flexible remote work

Job summary

Placements24 is seeking a forward-thinking Machine Learning Engineer to join their innovation hub in a fully remote capacity. You will design, build, and deploy production-ready ML systems against massive datasets. You will collaborate with data scientists and software engineers, optimize models for cloud environments, and stay on the cutting edge of ML algorithms.

A Master's or Ph.D. and 3+ years of hands-on experience are required.

Qualifications

• Master's or Ph.D. in Computer Science, AI, ML, or related field.
• 3+ years hands-on experience deploying ML models in production.
• Strong Python proficiency and ML libraries (TensorFlow, PyTorch, Scikit-learn, Keras).
• Experience with data processing and big data tech (Spark, Hadoop).
• Cloud familiarity (AWS, Azure, GCP) and MLOps practices.

Responsibilities

• Design, build, train, and deploy ML models for various applications.
• Develop and maintain robust ML pipelines for data processing and deployment.
• Collaborate with data scientists and software engineers to productionize models.
• Optimize models for performance, scalability, and cloud environments.
• Monitor model performance, drift, and retraining strategies.
• Research and evaluate new ML algorithms and tools.

Skills

Python

TensorFlow

PyTorch

Scikit-learn

Keras

Spark

Hadoop

AWS

Azure

GCP

MLOps

ML algorithms

Education

Master's or Ph.D. in Computer Science/AI/ML

Tools

TensorFlow

PyTorch

Scikit-learn

Keras

Spark

Hadoop

Job description

About the Role

Our client is seeking a forward-thinking and highly skilled Machine Learning Engineer to join their innovation hub in a fully remote capacity. This role is at the forefront of developing and deploying advanced machine learning models that drive intelligent solutions and enhance product capabilities. You will work with massive datasets, leveraging state-of-the-art algorithms and tools to build scalable, production-ready ML systems. This position offers the ultimate flexibility and the chance to contribute to groundbreaking projects from anywhere in the world, within a company that is committed to pushing the boundaries of artificial intelligence and fostering a culture of continuous learning and experimentation.

Key Responsibilities

• Design, build, train, and deploy machine learning models for various applications, including predictive analytics, natural language processing, and computer vision.
• Develop and maintain robust ML pipelines for data preprocessing, feature engineering, model training, evaluation, and deployment.
• Collaborate with data scientists and software engineers to integrate ML models into production systems and applications.
• Optimize ML models for performance, scalability, and efficiency in cloud-based environments.
• Monitor the performance of deployed models, identify drift, and implement retraining strategies as needed.
• Research and evaluate new ML algorithms, tools, and technologies to enhance the company's AI capabilities.

Requirements

• Master's or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
• 3+ years of hands‑on experience in building and deploying machine learning models in a production environment.
• Strong proficiency in Python and ML libraries such as TensorFlow, PyTorch, Scikit-learn, and Keras.
• Experience with data processing and big data technologies (e.g., Spark, Hadoop).
• Familiarity with cloud platforms (AWS, Azure, GCP) and MLOps best practices.
• Excellent understanding of ML algorithms, statistical modelling, and software engineering principles.

Benefits

• Highly competitive salary, commensurate with experience, plus significant performance bonuses.
• Global health, dental, and vision insurance coverage.
• Generous allowance for professional development, including courses, conferences, and certifications.
• Complete flexibility to work remotely from any location.
• Stock options and long‑term incentive plans.
• A dynamic, collaborative, and intellectually stimulating remote work environment focused on innovation.