Senior MLOps Engineer (Machine learning + DevOps)

Randstad; Singapore; Hybrid; SGD 80,000 - 100,000; Full time

Job summary

A well-known biotechnology research company in Singapore seeks an experienced AI/ML Engineer. This role involves maintaining AI models, developing pipelines, and automating processes within a hybrid work environment. Candidates should possess strong Python skills and experience with various ML frameworks and tools. An ideal candidate will have a background in machine learning operations with at least 3 years of relevant experience.

Benefits

Hybrid working arrangement

Base salary plus bonus

Shuttle bus service from multiple MRT stations

Qualifications

• Minimum 3 years in data or machine learning and operations, ideally in a hands-on MLOps role.
• Experience with ML frameworks and deployment tasks.
• Willingness to take early US calls if required.

Responsibilities

• Create and maintain code, documentation, testing and deployment frameworks for AI/ML models.
• Develop environments for managing AI models and data pipelines.
• Automate training and data/model management processes.

Skills

Machine learning model training pipeline

Python coding

Deployment of APIs

ML ops platforms

Unit testing and code reviews

Education

Bachelors in Computer Science or equivalent experience

Tools

MLFlow

Kubernetes

Docker

Tensorflow

Keras

Pytorch

XGBoost

Scikit-learn

Job description

about company

I am currently working with a well known biotechnology research company. Office located in Woodlands - but there's shuttle bus provided from multiple MRT stations.

Salary structure: Base + bonus! Hybrid working arrangement - 2 days WFH. Working hours 8am to 5pm. Can end work early and have more personal time. Might need to take 7am US calls.

about job

• Create and maintain code, documentation, testing and deployment frameworks, tools and infrastructure, working closely with engineers and domain experts on AI/ML models and pipelines
• Machine learning model training pipeline, how to manage the data, how to get data into production.
• Develop environments for building, testing, tracking production AI models and data across data pipelines
• Be a technical expert to develop AI models within a consistent ML environment, automate training and data/model management

skills and requirements

• Bachelors in Computer Science or equivalent experience
• Min 3 years in data or machine learning and operations, ideally in a hands‑on MLOps role
• Experience deploying APIs and packages
• Experience with ML ops platforms (MLFlow, Kubeflow, Kubernetes, Docker, dask, rapids.ai, Ray)
• Experience with ML frameworks (Tensorflow, keras, Pytorch, xgboost, sklearn)
• Strong Python coding skills – experience with unit testing, code reviews, version control
• Or could be DevOps Engineer with ML experience. OR Bioinformatics Engineer with AI/ML ops related experience OR ML Engineer with DevOps experience

To apply online please use the 'apply' function, alternatively you may contact Stella at 96554170 (EA: 94C3609 /R1875382)