Job Description

As a Machine Learning Engineer, you will bridge the gap between data science prototypes and production-grade machine learning systems. You will be responsible for deploying, scaling, and monitoring machine learning models in a production environment, ensuring reliability, performance, and maintainability across enterprise use cases.

What You’ll Do and How You’ll Succeed

Productionise ML models from Jupyter notebooks into scalable and reliable services.
Build feature engineering pipelines and feature stores for real-time and batch inference.
Implement model serving infrastructure, including REST APIs, batch scoring, and streaming inference.
Design and maintain CI/CD pipelines for ML models as part of MLOps practices.
Monitor model performance, detect drift, and trigger automated retraining where needed.
Optimise model inference for latency and cost through techniques such as model compression, quantisation, and caching.
Integrate ML models with existing systems such as CRM, billing, and campaign management platforms.

We’d Love to Hear From You If…

Experience

You have 4+ years of experience in software engineering, with 2+ years in ML engineering.

Technical Expertise

You have strong Python capability and solid software engineering practices, including testing, version control, and code review.
You have experience with containerisation technologies such as Docker and Kubernetes, as well as cloud deployment.
You are familiar with ML serving frameworks such as MLflow, Seldon, TensorFlow Serving, or Triton.
You have experience with Databricks, Spark, or similar distributed computing platforms.
You have knowledge of API design and microservices architecture.

Ways of Working

You can translate machine learning prototypes into production-ready systems with strong reliability and maintainability.
You take a structured approach to monitoring, optimisation, and operationalising ML models at scale.

Assignment Details

Location: McKinley, Taguig City
Work Set-Up: Hybrid

---

Who We Are

Thakral One is a consulting and technology services company headquartered in Singapore, with a pan-Asian presence. We focus primarily around technology-driven consulting, adoption of value-added bespoke solutions, enabling enhanced decision support through data analytics, and embracing possibilities in the cloud. We are heavily inclined towards building capabilities collaboratively with clients and believe strongly in improving grounded and practical outcomes.

This approach is possible through our partnership with leading global technology providers and internal R&D teams. Our clients come from Financial Services, Banking, Telco, Government, Healthcare, and Consumer-oriented organisations.