MLOps Engineer

Oxydata Software; Kuala Lumpur; Hybrid; MYR 150,000 - 200,000; Full time

Job summary

A leading data solutions firm is looking for an experienced Engineer Machine Learning, DevOps & Cloud Services in Kuala Lumpur. You will collaborate globally to maintain AI/ML products and analytics solutions, lead data science efforts, and program in Python. Ideal candidates will have a Bachelor’s degree and 4-7 years of relevant experience, focusing on cloud services. Join a team shaping sustainable future through technology in an inclusive environment.

Benefits

Mentoring opportunities

Hands-on experience with cloud-native AI platforms

Global teamwork

Qualifications

• 4-7 years of hands-on experience in data science or related fields with cloud services focus.
• Proficiency in Python with capability to learn other languages.
• Experience with SQL for database management.

Responsibilities

• Collaborate with global colleagues on AI/ML products and analytics solutions.
• Lead data science aspects while working with Data Engineers and AI Engineers.
• Program in Python and manage ML models using cloud technologies.

Skills

Python

Data science

Cloud services

SQL

Kubernetes

Docker

AI solutions

Education

Bachelor’s degree in Computer Science, Software Engineering, Information Systems

Master’s degree (nice-to-have)

Tools

Azure

Google Cloud Platform (GCP)

OpenShift

SQLAlchemy

FastAPI

Pydantic

Postgres

CI/CD pipelines

Git

Job description

Engineer Machine Learning, DevOps & Cloud Services
Job ID: 4RR4W45V
Location: Kuala Lumpur, Malaysia
Work Mode: [Onsite | Hybrid]
Job Type: [Permanent | Contract]

Our client is a Danish-based multinational with a global footprint, supplying stone wool solutions that support safer, more sustainable buildings and modern living. They operate 50+ factories and empower over 10,000 employees worldwide to drive impact through innovation and data. As a business at the forefront of digitalisation and AI adoption, they are investing heavily in advanced analytics, automation and AI platforms to shape a more sustainable future.

We are seeking an experienced Engineer Machine Learning, DevOps & Cloud Services to join the growing Data Science & Engineering team in Malaysia, working at the forefront of AI and machine learning and collaborating closely with colleagues in Malaysia, Denmark and Poland.

Responsibilities

• Work as part of the Data Science & Engineering team in Malaysia, collaborating with global colleagues to run and maintain AI/ML products and analytics solutions.

• Lead the data science aspects of the team and work closely with peers of varying skill sets (Data Engineers and AI Engineers).

• Program primarily in Python and use cloud technologies (Azure, Google Cloud, OpenShift) to deploy and manage ML models.

• Maintain and enhance custom AI products, including an in-house developed GPT-based solution.

• Develop and maintain AI APIs and backend services that power custom AI products and LLM solutions.

• Build and maintain back-end cloud applications using Kubernetes and Docker to serve as the backbone of AI products.

• Proactively respond to service requests and incidents to ensure high availability and continuous uptime of AI products in production.

• Profile, tune and optimise ML models and backend components to meet strict SLA and performance requirements.

• Evaluate and recommend new technologies, tools and architectural patterns to improve AI platforms and services.

• Automate infrastructure provisioning (IaC) and CI/CD pipelines for custom AI workloads.

• Guide and coach junior and mid-level engineers in Data Science, Software Engineering and AI platform development and maintenance.

• Innovate and continuously harden AI platforms against potential issues, ensuring robustness, reliability and scalability.

Requirements

Must-have:

• Bachelor’s degree in Computer Science, Software Engineering, Information Systems, or a related field.

• 4-7 years of hands‑on experience in data science or related fields with a strong focus on cloud‑based services.

• Proficiency in Python with the ability to pick up other programming languages as needed.

• Experience working with SQL.

Nice-to-have:

• Master’s degree in Computer Science, Software Engineering, Information Systems, or a related field.

• Experience with Python libraries such as SQLAlchemy, FastAPI and Pydantic.

• Exposure to OpenAI endpoints and experience working with LLMs.

• Knowledge of IT infrastructure (servers and databases).

• Experience with prompt engineering for AI/LLM solutions.

• Experience with Azure and Azure services related to data science.

• Knowledge of GCP and OpenShift.

• Knowledge of SAP.

• Experience with relational databases such as Postgres.

• Hands‑on experience with Kubernetes and Docker.

• Strong background with cloud services and modern deployment patterns.

• Experience with CI/CD pipelines.

• Extensive experience with Git, including GitHub and GitOps practices.

• Experience developing APIs that serve AI solutions.

• Excellent problem‑solving skills, detail‑oriented, and able to troubleshoot complex data issues under tight SLAs.

• Strong communication skills, able to liaise effectively with technical teams, non‑technical stakeholders and senior management.

• Proactive mindset with a continuous improvement attitude, able to break down ambiguous requirements into clear, actionable tasks.

Why Join Us

• Work closely with teammates across continents and be part of a positive, tight‑knit, global Data Science & Engineering community.

• Develop technology leadership skills by mentoring and guiding other engineers while growing your own expertise.

• Gain hands‑on experience with a modern tech stack including OpenShift, Kubernetes and cloud‑native AI platforms in a leading Danish‑based MNC.

• Empower business units across 50+ factories worldwide to embed AI into their workflows.

• Enable 10,000+ staff across the globe to use AI tools responsibly and effectively.

• Join a new and exciting team that is driving the AI agenda, fostering trust, literacy and responsible AI adoption.

• Contribute to global sustainability goals by applying AI to real‑world challenges that positively impact the planet.