Data Scientist Specialist

Posted 9 Days Ago
Be an Early Applicant
Ménaka, Gao, MLI
In-Office
Mid level
Digital Media • News + Entertainment
The Role
Architect, develop, and deploy production-grade ML/AI systems and pipelines (including GenAI, LLMs, and Computer Vision). Build scalable microservices/APIs, implement MLOps/CI-CD, monitor models, and integrate AI solutions with cross-functional teams and enterprise systems.
Summary Generated by Built In

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.

Skills Required

  • 4-7 years professional experience in Data Science or related technical fields
  • At least 3 years architecting and deploying production-grade ML models and pipelines
  • Proficiency in Python or R
  • Strong SQL skills, database concepts, and dimensional modeling
  • Experience with data transformation across relational and unstructured data stores
  • Experience with MLOps, automated model monitoring, and CI/CD for ML
  • Experience with containerization and orchestration (Docker, Kubernetes)
  • Version control experience (Git) and software engineering best practices
  • Experience building scalable production APIs or distributed batch processing systems
  • Applied experience with Generative AI, LLMs, RAG, and prompt engineering
  • Experience in Computer Vision and advanced statistical analysis
  • Strong analytical, critical thinking, communication, and teamwork skills; able to work under pressure
  • Background in Telecommunications industry or relevant business experience
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The Company

What We Do

Maxine is an award-winning nonfiction film and television studio founded by Mary Robertson, dedicated to creating journalist-and-filmmaker-driven nonfiction work.

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