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:

• Data Engineering and Data Analytics skills, with the ability to design and optimize processes for analyzing data
• Proficiency in Data Modeling and Data Warehousing concepts to ensure effective data organization and retrieval

𝐏𝐫𝐞𝐟𝐞𝐫𝐫𝐞𝐝:

• Excellent problem-solving abilities and strong communication skills to collaborate with cross-functional teams
• Experience supporting JupyterHub, MLflow, Airflow, or similar data science/ML tools.
• Knowledge of managing PostgreSQL, ClickHouse, or NoSQL databases in Kubernetes.
• Familiarity with dashboarding or data visualization platforms (e.g.,Grafana, Streamlit, Superset).
• Experience with data science and machine learning workflows.
• Proficiency in scripting languages like Bash or Python.

𝗦𝗼𝗳𝘁 𝗦𝗸𝗶𝗹𝗹𝘀:

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.

𝗪𝗵𝘆 𝗝𝗼𝗶𝗻 𝗨𝘀?

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