Machine Learning Engineer

Job Description

DataMinds Analytics is hiring a Machine Learning Engineer for our Singapore AI lab to productionise cutting-edge models for clients across Asia-Pacific. You will take models from research notebooks to robust, monitored production systems — building training pipelines, feature stores and inference services handling millions of predictions daily. Our Singapore lab serves clients across banking, retail and logistics, deploying models that personalise experiences for over a hundred million end users.

We sponsor visas, offer regional leadership opportunities, and work on genuinely advanced problems in NLP, vision and recommender systems. Our MLOps maturity is high: expect proper CI/CD for ML, feature platforms and a team that takes engineering rigour seriously. You will also evaluate emerging LLM infrastructure for client use cases, mentor junior MLOps engineers, and receive sponsorship for KubeCon and leading ML conferences.

Responsibilities

Design and build ML training and inference pipelines
Implement feature stores and model registries with versioning
Deploy models to Kubernetes with autoscaling and monitoring
Optimise model latency, throughput and cost in production
Collaborate with data scientists on model selection and evaluation
Establish MLOps best practices across client engagements

Requirements

4-7 years of ML engineering or applied ML experience
Strong Python and ML frameworks (PyTorch, TensorFlow)
Production experience with Kubernetes, Docker and cloud ML platforms
Knowledge of feature stores, model monitoring and drift detection
Familiarity with distributed training (Horovod, DeepSpeed)
Understanding of LLMs and vector databases is a plus

Skills

Python, PyTorch, TensorFlow, Kubernetes, MLflow, Kubeflow, AWS, Docker, SQL, Vector Databases

Benefits

Visa sponsorship with relocation to Singapore
Regional leadership and career growth opportunities
Annual bonus and employee share scheme
Comprehensive medical insurance
Cutting-edge AI conference sponsorship