Senior ML Engineer - Architect & Scale AI Pipelines

Thoughtworks; Singapore; On-site; SGD 110,000 - 180,000; Full time

Job summary

Thoughtworks Singapore seeks a Senior Machine Learning Engineer to design, build and maintain scalable ML architectures and infrastructure. You will collaborate with data scientists and engineers to translate business needs into effective ML systems, including pipelines, training, deployment, and monitoring.

You will drive technical discussions, mentor engineers, and explore the latest tools and frameworks to keep Thoughtworks at the forefront of ML practice.

Qualifications

• Proficient in writing clean, maintainable, testable code.
• Skilled in Python or Shell for automation and workflow optimization.
• Knowledge of distributed systems and scalable architectures for large ML apps.
• Experience with ML pipelines, model training, deployment and monitoring.
• Familiar with ML concepts and lifecycle, including MLOps and CI/CD.
• Hands-on experience with on-premise and cloud services for ML pipelines.

Responsibilities

• Design and drive robust, scalable ML architectures and infrastructure.
• Collaborate with data scientists and engineers to translate business needs into ML systems.
• Own development and maintenance of core ML functionalities and pipelines.
• Lead technical discussions, mentor engineers and ensure timely delivery.
• Explore new tools and frameworks to advance ML capabilities.
• Foster collaborative problem solving and mentor teammates.
• Contribute to ML strategy alignment with business objectives.
• Identify challenges and implement improvements in ML systems.

Skills

Python scripting

Shell scripting

Distributed systems

ML engineering

MLOps

Tools

Scikit-learn

TensorFlow

MLFlow

Kubeflow

PyTorch

Azure

AWS

GCP

Databricks

Job description

Thoughtworks Singapore seeks a Senior Machine Learning Engineer to design, build and maintain scalable ML architectures and infrastructure. You will collaborate with data scientists and engineers to translate business needs into effective ML systems, including pipelines, training, deployment, and monitoring.

You will drive technical discussions, mentor engineers, and explore the latest tools and frameworks to keep Thoughtworks at the forefront of ML practice.