Machine Learning Engineer

About the Role

We are looking for a seasoned Machine Learning Engineer to join a rapidly expanding technology firm, driving the development and scaling of machine learning solutions embedded within its products and platforms. This role offers a unique chance to work where machine learning intersects with software engineering and cloud infrastructure, guiding ML projects from experimental phases through to robust, scalable production deployments.

Responsibilities

• Design, develop, and deploy machine learning models and services in production environments.
• Collaborate closely with data scientists, software engineers, and product teams to embed ML capabilities into technology products.
• Build and maintain MLOps infrastructure including automated pipelines for model training, testing, deployment, monitoring, and retraining.
• Implement continuous integration and delivery (CI/CD) practices specific to machine learning workflows.
• Enhance model reliability and performance while developing scalable and efficient production infrastructure.
• Contribute to the design of ML platform architecture, focusing on model serving, automation, and observability to ensure scalable, secure, and efficient ML systems.

Requirements

• 6 to 10 years of experience as a Machine Learning Engineer with strong software engineering skills.
• Expertise in Python programming and hands-on experience with ML frameworks such as PyTorch, TensorFlow, or equivalent.
• Practical experience with MLOps including model deployment, CI/CD workflows, model monitoring, experiment tracking, containerization, and automated training and inference pipelines.
• Familiarity with container technologies like Docker and orchestration tools such as Kubernetes.
• Experience working with cloud platforms like AWS, Azure, or Google Cloud Platform.
• Knowledge of MLOps tools such as MLflow, Kubeflow, or similar technology stacks.
• Advantageous to have experience building scalable APIs, model serving infrastructure, and ML production platforms.

Additional Details

Applications should be sent directly to the recruitment contact provided. Only candidates shortlisted will be contacted due to a high number of applications.