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AI Python Engineer

Exclusive opportunity

Onsite

AI Python Engineer

Morgan McKinley

AI Python Engineer

Skills

Google Cloud PlatformSQL QueriesData EngineeringDockerFlaskPythonMicroservicesPyTorchTensorFlowGitGitLabMachine LearningAIAWSGitHubKubernetesNLP / Natural Language ProcessingFastAPIAzure

2 months ago

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Important information


Contract type:

Permanent

Salary:

MYR 96,000 – MYR 144,000 / year

Location:

Putrajaya, Malaysia

Work mode:

Onsite

Published on:

12 August 2026

What they need


Requested skills

Technical Skills :

  • Minimum 5 years of experience in Python development with an AI/ML focus

  • Proven experience in vibe coding with productive use of AI tools (GitHub Copilot, Cursor, Claude, ChatGPT)

  • Expertise in ML/DL frameworks: TensorFlow, PyTorch, Scikit-learn, Hugging Face, LangChain

  • Confirmed experience with LLMs (fine-tuning, prompt engineering, RAG, agents)

  • Proficiency with Cloud platforms (AWS SageMaker, Azure ML, GCP Vertex AI)

  • Knowledge of MLOps technologies and CI/CD pipelines for AI models

  • Skills in data engineering (preprocessing, feature engineering, data pipelines)

  • Proficiency in databases (SQL, NoSQL, Vector DBs)

  • Experience in API development (FastAPI, Flask, REST)

  • Good knowledge of containerisation (Docker, Kubernetes)

  • Expertise in testing and code quality (pytest, unittest, code coverage)

  • Knowledge of version control tools (Git, GitLab/GitHub)

  • Nice to have: Experience in Computer Vision and/or NLP

Expected deliverables

  • Participation in workshops with IT/business teams and Data Scientists

  • Development and optimisation of AI/ML models for business use cases

  • Integration and deployment of models in production (APIs, microservices)

  • Expert use of vibe coding to accelerate development without compromising quality

  • Implementation of MLOps pipelines (training, versioning, monitoring)

  • Automated testing and validation of models (performance, robustness, bias)

  • Detailed technical documentation (code, models, APIs, reusable prompts)

  • Performance optimisation (latency, costs, scalability)

  • Technology watch and recommendations on new AI techniques

  • Sharing of vibe coding best practices with the tea

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