Data Scientist Specialist

Maxine; Malaysia; In loco; MYR 180.000 - 260.000; Tempo pieno

Descrizione del lavoro

Maxis is seeking a Data Scientist - ML & AI Engineer Specialist in Malaysia to architect and deploy production‑grade AI systems and scalable ML pipelines. You will own the end‑to‑end engineering lifecycle from model development to ML Ops, ensuring robust, automated, and integrated AI solutions that drive measurable business impact.

The role emphasizes Generative AI, LLMs, CV, and collaboration with Data Engineers and DevOps to embed AI into broader software ecosystems.

Competenze

• 4–7 years of professional experience in Data Science or related fields.
• 3+ years building production‑grade ML models and AI pipelines.
• Strong skills in SQL, data modeling and analytics.

Mansioni

• Machine Learning Systems & Architecture: Architect end‑to‑end ML systems with Python or R.
• Production‑Grade AI Deployment: Design robust AI pipelines and microservices for low latency.
• ML Ops & Model Lifecycle Management: Implement automated monitoring and CI/CD for ML.
• Applied AI Research & Innovation: Prototype Generative AI, LLMs and CV into products.
• Cross‑Functional Systems Integration: Collaborate with Data Engineers and DevOps.
• Engineering Excellence & Documentation: Enforce Git, Docker/Kubernetes, and thorough docs.

Conoscenze

Python/R

ML Systems

SQL

MLOps

Docker/Kubernetes

LLMs

NLP/Computer Vision

Git

Strumenti

Docker

Kubernetes

Git

Descrizione del lavoro

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.