Machine Learning Intern

GrowthOps Asia; Kuala Lumpur; On-site; MYR 28,000 - 39,000; Full time

Job summary

AppliedAI in Malaysia is seeking an Opus ML Engineer Intern to support the development and improvement of our AI infrastructure under the guidance of senior engineers.

You'll gain hands‑on experience building and maintaining inference pipelines, workflow orchestration, prompt design, and agentic integrations powering Opus’s AI features.

This role is ideal for recent graduates or final‑year students eager to apply academic knowledge to real‑world AI systems and grow into a full ML engineering role.

Qualifications

• Recently completed (or completing) a degree in Math, Computer Science, Machine Learning, Data Science, Software Engineering, or a related field.
• Solid understanding of Python and general software engineering principles.
• Familiarity with machine learning concepts and frameworks (e.g. PyTorch, TensorFlow, scikit‑learn, or HuggingFace).
• Interest or coursework in LLMs, NLP, prompt engineering, or generative AI.
• Basic understanding of APIs, version control (Git), and command‑line tools.
• Exposure to cloud platforms (AWS, GCP, or Azure) or containerization (Docker, Kubernetes) is a plus.
• Strong willingness to learn, take feedback, and work in a fast‑paced environment.

Responsibilities

• Assist in designing, developing and maintaining AI inference and orchestration pipelines used in production.
• Support model‑serving optimization efforts around performance, latency, and reliability.
• Help implement observability, logging, and monitoring for AI components.
• Contribute to prompt engineering and alignment experiments to improve response quality and consistency.
• Write clean, well‑documented code and assist in refactoring existing codebases for modularity and clarity.
• Collaborate with senior engineers and product teams to deliver stable, user‑facing AI features.
• Participate in code reviews, testing, and documentation efforts.

Skills

Python

ML concepts

LLMs/NLP

APIs

Git

Cloud platforms

Education

Bachelor’s or higher in Math, CS, ML, Data Science, SE

Tools

PyTorch

TensorFlow

scikit-learn

HuggingFace

Docker

Kubernetes

Job description

AppliedAI is a pioneering AI technology company committed to innovation and excellence in artificial intelligence solutions in regulated industries such as healthcare, insurance, government, and financial services.

Opus is the world's first Knowledge Work AI platform. Built by AppliedAI to pioneer Supervised Automation, a human-in-the-loop model where AI handles repetitive, structured tasks while human experts provide crucial oversight at defined intervals.

The platform uses its proprietary Large Work Model to generate and orchestrate outcome-based workflows, enabling a dramatic reduction in the cost of knowledge work and allowing human talent to focus on high-value, creative, and judgement-intensive activities.

Overview

As an Opus ML Engineer Intern, you will support the development and improvement of Opus's AI infrastructure under the guidance of senior engineers.

You'll be gaining hands‑on experience building and maintaining the systems that power Opus's AI features, from inference pipelines and workflow orchestration to prompt design and agentic integrations.

This role is ideal for recent graduates or final‑year students eager to apply their academic knowledge to real‑world AI systems and grow into a full ML engineering role.

Responsibilities

• Assist in designing, developing and maintaining AI inference and orchestration pipelines used in production.
• Support model‑serving optimization efforts around performance, latency, and reliability.
• Help implement observability, logging, and monitoring for AI components.
• Contribute to prompt engineering and alignment experiments to improve response quality and consistency.
• Write clean, well‑documented code and assist in refactoring existing codebases for modularity and clarity.
• Collaborate with senior engineers and product teams to deliver stable, user‑facing AI features.
• Participate in code reviews, testing, and documentation efforts.

Qualifications

• Recently completed (or completing) a degree in Math, Computer Science, Machine Learning, Data Science, Software Engineering, or a related field.
• Solid understanding of Python and general software engineering principles.
• Familiarity with machine learning concepts and frameworks (e.g. PyTorch, TensorFlow, scikit‑learn, or HuggingFace).
• Interest or coursework in LLMs, NLP, prompt engineering, or generative AI.
• Basic understanding of APIs, version control (Git), and command‑line tools.
• Exposure to cloud platforms (AWS, GCP, or Azure) or containerization (Docker, Kubernetes) is a plus.
• Strong willingness to learn, take feedback, and work in a fast‑paced environment.

Bonus

• Personal projects, hackathon experience, or open‑source contributions related to ML/AI.
• Familiarity with orchestration tools (Airflow, Celery) or CI/CD pipelines.
• Experience with observability or monitoring tools.
• Opportunity to work with a highly innovative AI technology company.
• Collaborative and innovative work environment.
• Growing, entrepreneurial and forward‑thinking culture.
• Career growth and professional development opportunities.

We appreciate your application and will be in touch with shortlisted candidates regarding next steps