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WM

Data Scientist Specialist

wd3:maxine:maxis-career
Location not stated
2 months ago
  • AI
  • Machine Learning
  • Python
  • Natural Language Processing
  • Computer Vision
  • Microservices
  • CI/CD
  • MLOps
  • Devops
  • Git
  • Docker
  • Kubernetes
  • Large Language Models
  • RAG
  • SQL
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Are you ready to get ahead in your career?

  • We want to empower you to turn your ambitions into achievements.
  • We thrive in inclusiveness, diversity and embrace close collaborations for you to create impact for yourself and others.
  • Together, we aim to bring the best of technology to help people, businesses and the nation to be ahead in a changing world.
  • To realise our vision to become Malaysia’s leading converged solutions company, we are looking for a new talent to innovate and grow with us in a culture that values commitment, performance and possibilities.

Why does this job exist and why is it critical?​

The Data Scientist - ML & AI Engineer Specialist is responsible for architecting and deploying production-grade AI systems and scalable machine learning pipelines. This role focuses on the end-to-end engineering lifecycle -from advanced model development to ML Ops - ensuring that AI solutions are robust, automated, and seamlessly integrated into the organization's technical ecosystem to drive measurable business impact.

What are you accountable for?

  • Machine Learning Systems & Architecture:Architect and develop end-to-end ML systems using Python or R. Beyond EDA, focus on building modular, reusable codebases for predictive modeling, recommendation engines, and advanced NLP/Computer Vision architectures.

  • Production-Grade AI Deployment:Design and implement robust, scalable AI pipelines and microservices. Focus on transitioning models from experimental notebooks to high-availability production environments (Real-time APIs or distributed batch processing) ensuring low-latency and high throughput.

  • ML Ops & Model Lifecycle Management:Implement automated model monitoring and CI/CD for ML (MLOps). Track performance metrics and data drift in production, ensuring systems are self-healing, scalable, and maintain high reliability under varying load conditions.

  • Applied AI Research & Innovation:Prototype and integrate state-of-the-art AI advancements - specifically Generative AI, LLMs, and Computer Vision - into existing product stacks to solve domain-specific problems and maintain a technological edge.

  • Cross-Functional Systems Integration:Partner with business stakeholders to define technical requirements and collaborate deeply with Data Engineers and DevOps to ensure AI solutions are seamlessly integrated into the broader software ecosystem.

  • Engineering Excellence & Documentation:Champion software engineering best practices within the AI team, including version control (Git), containerization (Docker/Kubernetes), and comprehensive system documentation for reproducibility and technical scalability.

  • Generative AI Engineering:Architect solutions leveraging Large Language Models (LLMs) through prompt engineering, fine-tuning, and Retrieval-Augmented Generation (RAG) to deliver high-quality, context-aware AI applications.

What do you need to have to fit this role?

  • A minimum of 4-7 years of professional experience in Data Science or related technical fields, with at least 3 years dedicated to architecting and deploying production-grade ML models and AI pipelines within complex enterprise ecosystems.

  • Highly proficiency in end-to-end AI development, including Gen AI, Computer Vision, and advanced statistical analysis.

  • Strong command of SQL, database concepts, and dimensional modeling. Experienced in data transformation methods across various data structures, including relational and unstructured data stores.

  • Possesses robust analytical and critical thinking skills.

  • A passionate self-starter who is highly dedicated and capable of working independently.

  • A strong team player with excellent interpersonal communication skills, proven ability to perform effectively under pressure, and dedicated to delivering results on time.

  • A background combining Telecommunication industry knowledge with relevant business experience is highly desirable.

What’s next?

  • Once you’ve applied online, our team will carefully review your application. Due to a high volume of applications, we appreciate your patience to allow for a fair and timely review process.
  • Should you be shortlisted for the role, we will send you an invitation via email for a digital interview. You can also check on your application status by logging into your candidate account.

Maxis values diverse voices & people. We hire and reward our employees based on capability & performance — regardless of ethnicity, gender, age, education, religion, nationality or physical ability.

Data Scientist Specialist · wd3:maxine:maxis-career

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