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Machine Learning Data Engineer
Kuala Lumpur, Malaysia
Full-Time
You will love it
Hybrid
Posted 2w ago
Specialty:
Machine Learning Engineer
Experience Level:
4-6 years
Management Level:
6-10 people
English Level:
Fluent
Skills & Technologies
AWS
TensorFlow
Azure
Kubernetes
Machine Learning
PyTorch
Problem Solving
Apache Kafka
Apache Hadoop
Spark (Java)
Computer Vision
Data Mining
GCP (Google cloud platform)
Data Analysis
Communication Skills
Cross-functional Collaboration
About the Job
Our client is a leading food manufacturer in Australia and New Zealand, with a workforce of over 6,000 employees operating across 60 sites. Committed to innovation and quality, they play a vital role in delivering high-quality products to millions of consumers. The team makes some of Australia & New Zealand's favourite & most innovative products, living the core purpose of ‘to delight people every day with the food they love!'
As a Machine Learning Data Engineer, you will be at the forefront of developing and deploying AI-driven solutions that power business intelligence and automation. This role is an exciting opportunity to work with state-of-the-art AI frameworks, cloud platforms, and MLOps processes, ensuring that machine learning models are scalable, efficient, and seamlessly integrated into production environments. You will collaborate closely with data scientists, data engineers, and business teams to drive innovation and maximize the impact of AI solutions across the organization.
As a Machine Learning Data Engineer, you will be at the forefront of developing and deploying AI-driven solutions that power business intelligence and automation. This role is an exciting opportunity to work with state-of-the-art AI frameworks, cloud platforms, and MLOps processes, ensuring that machine learning models are scalable, efficient, and seamlessly integrated into production environments. You will collaborate closely with data scientists, data engineers, and business teams to drive innovation and maximize the impact of AI solutions across the organization.
Responsibilities
- Build, train, and deploy scalable ML models using AWS SageMaker, TensorFlow, PyTorch, and related frameworks.
- Automate ML workflows, ensuring minimal manual intervention and efficient model retraining and monitoring.
- Develop and optimize ML pipelines for real-time and batch processing.
- Implement MLOps best practices, ensuring seamless model deployment, versioning, and monitoring.
- Collaborate with data engineers to integrate ML models into production environments.
- Ensure AI governance, compliance, and security standards are met.
- Troubleshoot ML model performance issues and optimize for efficiency and scalability.
Minimum Qualifications
- Bachelor's degree in Business, Computer Science, Information Technology, or a related field.
- 5–10 years of experience in machine learning model development and deployment.
- Proficiency in Python and ML frameworks such as TensorFlow, PyTorch, or Keras.
- Experience working with cloud platforms (AWS preferred, Azure, GCP).
- Strong understanding of ML model lifecycle, from training to production deployment.
- Hands-on experience with MLOps tools (Kubeflow, MLflow, AWS SageMaker).
- Familiarity with big data technologies for ML (Spark, Hadoop, Kafka).
- Strong problem-solving skills and ability to work in cross-functional teams.
- Excellent communication skills, with the ability to explain ML concepts to technical and non-technical stakeholders.
Benefits
- A diverse, inclusive, and supportive company culture.
- Competitive remuneration.
- Opportunity to collaborate and work with global clients and stakeholders.
- Medical benefits.
- Great Paid Leave entitlements.
- Team outings, travel opportunities, company parties/events, and other exciting activities.
- Exposure to an international environment, working with people across Malaysia, Vietnam, the Philippines, and Australia.
- Industry and role-related training.
- Ongoing career opportunities.
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