Senior Machine Learning Engineer [up to 20k]

Agensi Pekerjaan Randstad Sdn Bhd - Professional; Kuala Lumpur; On-site; MYR 150,000 - 200,000; Full time

Job summary

A leading recruitment agency in Kuala Lumpur seeks a Senior Machine Learning Engineer to design, train, and deploy production-grade ML models. The ideal candidate will have strong proficiency in Python and ML libraries, experience with deep learning frameworks such as PyTorch, and knowledge of cloud platforms like AWS. This role involves building CI/CD pipelines and leveraging advanced NLP techniques. Competitive salary offered up to 20k.

Qualifications

• Proficiency in Python and ML libraries such as Scikit-learn, Pandas, and XGBoost.
• Strong experience with deep learning frameworks like PyTorch.
• Hands-on experience building with LLMs, including prompting, RAG, and fine-tuning.
• Experience with Hugging Face for sourcing and implementing pre-trained models.
• Strong skills in cloud platforms, preferably AWS.

Responsibilities

• Design, train, and deploy production-grade ML models.
• Build robust, automated CI/CD pipelines for model training and serving.
• Collaborate to manage data pipelines for ML workflows ensuring data quality.
• Leverage LLMs and advanced NLP techniques for insights extraction.

Skills

Python

Scikit-learn

Pandas

XGBoost

PyTorch

AWS

Tools

Docker

Kubernetes

Hugging Face

Job description

Senior Machine Learning Engineer [up to 20k]

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• design, train, and deploy production‑grade ML models.
• build robust, automated CI/CD pipelines for model training, evaluation, and serving using containerization (Docker, Kubernetes) and cloud‑native tools.
• collaborate with other teams to build and manage the data pipelines necessary for ML workflows, ensuring data quality and integrity from various sources.
• leverage LLMs and advanced NLP techniques to extract insights from unstructured data, automate complex business processes, and build intelligent solutions

Knowledge, skills and experience

• proficiency in Python and ML libraries (e.g., Scikit‑learn, Pandas, XGBoost).
• strong experience with deep learning frameworks (PyTorch).
• hands‑on experience building with LLMs, including prompting, RAG, and fine‑tuning.
• experience with Hugging Face for sourcing, fine‑tuning, and implementing pre‑trained models for NLP and other tasks.
• strong skills in cloud platforms, preferably AWS.