Machine Learning Engineer

Placements24; Cape Town; Presencial; ZAR 600.000 - 900.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Competitive salary

Bonus

Health benefits

Hybrid work model

Professional growth

Cape Town office

Descripción de la vacante

Placements24 is seeking a talented Machine Learning Engineer to join its Cape Town team. You will design, build, and deploy ML models and systems that drive critical business decisions and enhance product capabilities.

A hybrid work model combines in-office collaboration with remote work. You will work with data scientists, software engineers, and product managers to translate complex data into actionable insights and robust ML solutions, with opportunities for growth and exposure to

Formación

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• 3+ years of experience as a Machine Learning Engineer or similar role.
• Proficiency in Python and ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch).
• Experience with cloud platforms like AWS, Azure, or GCP for ML workloads.
• Familiarity with big data technologies such as Spark, Hadoop, or similar.
• Understanding of software engineering best practices, including version control and CI/CD.

Responsabilidades

• Develop, train, and deploy scalable machine learning models using various algorithms.
• Implement and manage MLOps pipelines for model versioning, deployment, and monitoring.
• Collaborate with data scientists to translate research models into production-ready code.
• Optimize ML models for performance, scalability, and efficiency in a production environment.
• Work with big data technologies to process and prepare datasets for model training.
• Contribute to the design and architecture of machine learning systems and infrastructure.

Conocimientos

Python

Scikit-learn

TensorFlow

PyTorch

CI/CD

Version Control

MLOps

Problem Solving

Educación

Bachelor's or Master's in Computer Science/Engineering

Herramientas

AWS

Azure

GCP

Spark

Hadoop

Descripción del empleo

About the Role

Our client is looking for a talented Machine Learning Engineer to join their dynamic team in Cape Town . You will play a key role in designing, building, and deploying machine learning models and systems that drive critical business decisions and enhance product capabilities. This role involves working closely with data scientists, software engineers, and product managers to translate complex data into actionable insights and robust ML solutions. We offer a hybrid work model, combining the benefits of in-office collaboration with the flexibility of remote work, fostering a productive and engaging environment within our innovative tech hub.

Key Responsibilities

• Develop, train, and deploy scalable machine learning models using various algorithms.
• Implement and manage MLOps pipelines for model versioning, deployment, and monitoring.
• Collaborate with data scientists to translate research models into production-ready code.
• Optimize ML models for performance, scalability, and efficiency in a production environment.
• Work with big data technologies to process and prepare datasets for model training.
• Contribute to the design and architecture of machine learning systems and infrastructure.

Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• 3+ years of experience as a Machine Learning Engineer or similar role.
• Proficiency in Python and ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch).
• Experience with cloud platforms like AWS, Azure, or GCP for ML workloads.
• Familiarity with big data technologies such as Spark, Hadoop, or similar.
• Understanding of software engineering best practices, including version control and CI/CD.

Benefits

• Competitive salary and attractive bonus structure.
• Comprehensive health and wellness benefits package.
• Hybrid work model offering flexibility and work-life balance.
• Opportunities for professional growth and continuous learning.
• Access to cutting-edge technology and a collaborative work environment.
• Convenient office location in Cape Town with modern amenities.