
Cedaris offers an AI-powered platform that helps pharma and chemical manufacturers optimize processes and reduce waste. It uses AI for process simulation, optimization, and predictive analytics,β¦

Cedaris offers an AI-powered platform that helps pharma and chemical manufacturers optimize processes and reduce waste. It uses AI for process simulation, optimization, and predictive analytics,β¦
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Company Description
Cedaris Pte Ltd empowers pharmaceutical and chemical manufacturers with an AI-driven software platform focused on process simulation, optimization, and predictive analytics. By integrating advanced technology with sustainable and modular manufacturing principles, the company enables partners to improve efficiency, reduce waste, and foster innovation in API production. Cedaris also conducts market research, analyzes competitive landscapes, and evaluates customer needs and regulatory environments for tailored solutions. Cedaris stands at the intersection of cutting-edge technology and sustainable manufacturing to drive progress for its clients.
Role Description
This is a full-time hybrid role for a Kubernetes Engineer - Data Science Platform Support, based in Singapore with some flexibility for remote work. The engineer will be responsible for developing, deploying, and maintaining Kubernetes clusters that support the company's data science platform. Key tasks will include managing scalable and reliable data storage, monitoring platform performance, troubleshooting issues, and automating deployment pipelines. The role also involves collaborating closely with data scientists and developers to ensure seamless platform usage and supporting the implementation of new tools and technologies as needed. We are seeking a skilled Kubernetes Engineer to support our growing data science infrastructure, which includes containerized notebooks
(e.g., JupyterHub), dashboards (e.g., Grafana, Streamlit), and databases
(e.g., PostgreSQL, ClickHouse, MongoDB). You will play a key role in
ensuring high availability, performance, and security of our Kubernetes-
based platform that enables our data scientists and analysts to do
impactful work at scale.
Qualifications:
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Strong problem-solving skills and ability to troubleshoot complex
system issues.
Effective communicator who can collaborate across engineering and
data science teams.
Self-motivated and eager to learn emerging tools and technologies.
Ability to document infrastructure and support runbooks clearly.
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Work in a data-driven company empowering real-time decision-making .Influence the design of a modern data platform from the ground up. Collaborate with top-tier data scientists and engineers. Be at the forefront of AI/IoT in the pharma manufacturing and Lab of tomorrow