Machine Learning Engineer - Predictive Analytics

Placements24; Durban; Híbrido; ZAR 400.000 - 700.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Health insurance

Generous paid time off

Performance-based bonus

Professional growth opportunities (e.g

Online courses and conferences

Descripción de la vacante

Placements24 in Durban, South Africa, is seeking a Machine Learning Engineer to design, deploy, and maintain scalable ML systems. The role emphasizes end-to-end responsibilities from preprocessing to deployment while handling large datasets and collaborating with stakeholders.

Ideal candidates will have 3+ years of production ML experience, strong Python skills, and hands-on experience with ML libraries and cloud platforms.

Formación

• Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a related quantitative field.
• Proven experience (3+ years) in developing and deploying machine learning models in a production environment.
• Strong understanding of machine learning algorithms (regression, classification, clustering, etc.) and statistical modeling.
• Proficiency in Python and relevant ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch, Keras).
• Experience with data manipulation and analysis tools (e.g., Pandas, NumPy).
• Familiarity with SQL and database systems.
• Experience with cloud computing platforms (e.g., AWS SageMaker, Azure ML, GCP AI Platform).
• Knowledge of MLOps principles and tools is highly desirable.
• Strong problem-solving abilities and attention to detail.
• Excellent communication skills, with the ability to explain complex technical concepts to non-technical audiences.

Responsabilidades

• Design, build, train, and deploy machine learning models for predictive analytics, forecasting, and classification tasks.
• Develop and maintain robust data pipelines for feature engineering and model training.
• Implement and optimize machine learning algorithms, ensuring scalability and efficiency.
• Collaborate with data scientists and business stakeholders to understand requirements and translate them into technical solutions.
• Monitor and evaluate the performance of deployed models, iterating and retraining as needed.
• Utilize cloud platforms (e.g., AWS, Azure, GCP) for model development and deployment.
• Write clean, maintainable, and well-documented code in Python or other relevant languages.
• Stay up-to-date with the latest advancements in machine learning and AI.
• Contribute to the development of best practices and MLOps strategies within the team.
• Troubleshoot and resolve issues related to ML models and infrastructure.

Conocimientos

Python

Machine learning

Problem solving

Communication

Educación

Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or related field

Herramientas

Scikit-learn

TensorFlow

PyTorch

Keras

Pandas

NumPy

SQL

AWS SageMaker

Azure ML

GCP AI Platform

Descripción del empleo

About the Role

Our client is at the forefront of leveraging data to drive business insights and is seeking a talented Machine Learning Engineer to join their innovative team. This role is based out of our Durban, KwaZulu-Natal office, and is offered on a fully remote basis, allowing you to work from anywhere in South Africa. You will play a crucial role in developing, deploying, and maintaining machine learning models that tackle complex business challenges, focusing on predictive analytics. This is a fantastic opportunity to work with large datasets, cutting-edge technologies, and collaborate with a team of experts dedicated to advancing data science. The ideal candidate will have a strong foundation in machine learning principles, excellent programming skills, and a passion for building scalable and reliable ML systems. You will be responsible for the entire ML lifecycle, from data preprocessing and feature engineering to model training, evaluation, and deployment. We are looking for someone who is not only technically proficient but also a proactive problem-solver and an effective communicator.

Key Responsibilities

• Design, build, train, and deploy machine learning models for predictive analytics, forecasting, and classification tasks.
• Develop and maintain robust data pipelines for feature engineering and model training.
• Implement and optimize machine learning algorithms, ensuring scalability and efficiency.
• Collaborate with data scientists and business stakeholders to understand requirements and translate them into technical solutions.
• Monitor and evaluate the performance of deployed models, iterating and retraining as needed.
• Utilize cloud platforms (e.g., AWS, Azure, GCP) for model development and deployment.
• Write clean, maintainable, and well-documented code in Python or other relevant languages.
• Stay up-to-date with the latest advancements in machine learning and AI.
• Contribute to the development of best practices and MLOps strategies within the team.
• Troubleshoot and resolve issues related to ML models and infrastructure.

Requirements

• Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a related quantitative field.
• Proven experience (3+ years) in developing and deploying machine learning models in a production environment.
• Strong understanding of machine learning algorithms (regression, classification, clustering, etc.) and statistical modeling.
• Proficiency in Python and relevant ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch, Keras).
• Experience with data manipulation and analysis tools (e.g., Pandas, NumPy).
• Familiarity with SQL and database systems.
• Experience with cloud computing platforms (e.g., AWS SageMaker, Azure ML, GCP AI Platform).
• Knowledge of MLOps principles and tools is highly desirable.
• Strong problem-solving abilities and attention to detail.
• Excellent communication skills, with the ability to explain complex technical concepts to non-technical audiences.

Benefits

• Our client offers a competitive salary.
• Comprehensive health insurance.
• Generous paid time off.
• As this is a fully remote role, you will enjoy the flexibility and convenience of working from home.
• A performance-based bonus structure is also in place.
• We provide opportunities for professional growth, including access to online courses, workshops, and industry conferences.
• Join our client in Durban and be part of a forward-thinking company that is making a significant impact through data-driven innovation.
• We offer a supportive and collaborative work environment focused on continuous learning and development.