Azure Machine Learning Engineer

Cognizant; Kuala Lumpur; On-site; MYR 90,000 - 140,000; Full time

Job summary

A leading technology firm is seeking an experienced Azure Machine Learning Engineer in Kuala Lumpur, Malaysia. This role requires strong expertise in designing, developing, and deploying machine learning models to address business challenges. Ideal candidates will have 5-14 years of experience and a Bachelor's or Master's in a relevant field. Proficiency in Python or R, machine learning libraries, and cloud platforms like AWS, Azure, and GCP is essential, along with excellent problem-solving abilities and communication skills.

Qualifications

• 5-14 years of experience in relevant field.
• Strong proficiency in Python (or R) and ML libraries.
• Solid understanding of algorithms, statistics, and data structures.

Responsibilities

• Design and implement machine learning algorithms for predictive analytics.
• Preprocess and analyze large datasets.
• Build, train, and evaluate models using ML frameworks.
• Deploy models into production and monitor performance.
• Collaborate with data engineers and software developers.

Skills

Python or R

Machine Learning Libraries (TensorFlow, PyTorch, Scikit-learn)

Algorithms

Statistics

Data Structures

Cloud Platforms (AWS, Azure, GCP)

Containerization (Docker, Kubernetes)

Data Preprocessing

Feature Engineering

Model Evaluation Techniques

Education

Bachelor’s or Master’s degree in Computer Science, Data Science, or related field

Job description

Azure Machine Learning Engineer

Location: KL, Malaysia

Experience: 5-14 Years

Role Overview

We are seeking a highly skilled Machine Learning Engineer to design, develop, and deploy machine learning models that solve real-world business problems. The ideal candidate will have strong expertise in data science, programming, and model optimization.

Key Responsibilities

• Design and implement machine learning algorithms for predictive analytics and automation.
• Preprocess and analyze large datasets to extract meaningful insights.
• Build, train, and evaluate models using frameworks such as TensorFlow, PyTorch, or Scikit-learn.
• Deploy models into production environments and monitor performance.
• Collaborate with data engineers and software developers to integrate ML solutions into applications.
• Stay updated with the latest advancements in AI/ML technologies and tools.
• Build ML models to validate issue resolution tagging.
• Compare transcription of issue raised vs closure remark vs actual root cause.
• Provide % accuracy of correctly tagged resolutions.
• Experience in data ingestion, transformation, and orchestration.
• Understanding of data pipelines and governance.
• Ability to prepare large datasets for BI and ML consumption.

Required Skills & Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Science, or related field.
• Strong proficiency in Python (or R), and experience with ML libraries (TensorFlow, PyTorch, Scikit-learn).
• Solid understanding of algorithms, statistics, and data structures.
• Experience with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes).
• Knowledge of data preprocessing, feature engineering, and model evaluation techniques.
• Excellent problem-solving and communication skills.

Preferred Qualifications

• Experience with NLP, computer vision, or deep learning.
• Familiarity with MLOps tools and practices.
• Prior experience in deploying ML models at scale.

About Cognizant

Cognizant (Nasdaq: CTSH) engineers modern businesses. We help our clients modernize technology, reimagine processes and transform experiences so they can stay ahead in our fast-changing world. Together, we're improving everyday life. See how at www.cognizant.com or @cognizant.

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