Machine Learning Engineer

SNSoft Sdn Bhd; Kuala Lumpur; On-site; MYR 250,000 - 300,000; Full time

Job summary

A leading technology firm in Kuala Lumpur is looking for a Machine Learning Engineer to design and deploy innovative machine learning models. This role involves collaborating with teams to enhance customer service and product offerings. Ideal candidates should have a Bachelor's or Master's degree in a related field, with at least 3 years of experience in machine learning, proficiency in Python, and familiarity with frameworks like TensorFlow and PyTorch. Competitive compensation is offered.

Benefits

Competitive salary range (MYR6,000 - MYR10,000)

Project Incentive

Sports Activities

Training and certification sponsorship

Health claims for Optical, Dental, Body Check Up

Qualifications

• Minimum 3 years experience as a Machine Learning Engineer or similar role.
• Strong understanding of data management and processing tools.

Responsibilities

• Design, build, and maintain scalable machine learning models.
• Collaborate with cross-functional teams to deliver solutions.
• Monitor model performance in production.

Skills

Python

Machine Learning Frameworks

Data Management

Data Analysis Tools

Problem-Solving

NLP Experience

Education

Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, Statistics

Tools

TensorFlow

PyTorch

SQL

Hadoop

Spark

Job description

At SNSoft, we're at the forefront of technological advancement, integrating cutting‑edge solutions into everyday life. Our culture thrives on innovation, collaboration, and a commitment to excellence. We foster an inclusive environment where every team member's contribution is valued and where everyone has the opportunity to grow.

Benefits and Compensation

• Competitive salary range (MYR6,000- MYR10,000 per month, depending on experience).
• Project Incentive (upon Company Declaration based on project performance).
• Sports Activities (Badminton & Basketball), Company Outing.
• Training and certification sponsored by company (Selected employees).
• Optical, Dental, Body Check Up Claim (upon Confirmation).

Job Summary

As a Machine Learning Engineer, your responsibilities will include designing, developing, and deploying machine learning models and algorithms to address complex challenges and improve our products and services. Additionally, you will play a key role in AI‑enhanced customer service. You will collaborate closely with data scientists, software engineers, and domain experts to implement state‑of‑the‑art machine learning solutions.

Key Responsibilities

• Model Development: Design, build, and maintain scalable machine learning models and algorithms.
• Data Analysis: Analyze and preprocess data from various sources to prepare it for model training.
• Model Training & Evaluation: Train, validate, and tune machine learning models to achieve optimal performance.
• Deployment: Deploy models into production and integrate them with existing systems.
• Monitoring & Maintenance: Monitor model performance in production and update models as necessary to ensure they remain accurate and relevant.
• Collaboration: Work with cross‑functional teams, including data scientists, software engineers, and product managers, to understand requirements and deliver solutions.
• Research: Stay current with the latest developments in machine learning and AI to continuously improve our technology stack.

Required Qualifications

• Education: Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, Statistics, or a related field.
• Experience: Demonstrated at least 3 years experience as a Machine Learning Engineer or in a similar role.
• Programming Skills: Expertise in programming languages such as Python, golang, or Java.
• Machine Learning Frameworks: Proficient with machine learning frameworks and libraries like TensorFlow, PyTorch, JAX, scikit‑learn, or equivalent.
• Data Management: Strong understanding of data management and processing tools such as SQL, Hadoop, Spark, etc.
• Problem‑Solving: Exceptional analytical and problem‑solving abilities.
• Data Analysis Tools: Skilled in using data analysis and visualization tools like NumPy, Pandas, and Matplotlib.
• NLP Experience: Familiarity with natural language processing concepts and large language models, including transformers and attention mechanisms.

Preferred Qualifications

• Advanced Education: Ph.D. in a relevant field.
• Domain Knowledge: Experience in specific domains such as natural language processing (NLP), recommendation systems, computer vision, etc.
• Big Data: Experience with big data technologies and distributed computing.
• Cloud Services: Familiarity with cloud platforms such as AWS, Google Cloud, or Azure.
• DevOps: Knowledge of CI/CD pipelines and tools for automating the deployment of machine learning models.