Production-Driven Speech ML Engineer (Multilingual)

VALSEA; Singapore; On-site; SGD 120,000 - 160,000; Full time

Job summary

VALSEA is seeking an applied ML engineer to own end-to-end improvements in speech and ASR under real production constraints in Singapore. You will push models from experiments into deployed systems, focusing on multilingual and code-switching scenarios with diverse data and latency/cost limits.

You will collaborate with engineers to optimize inference, memory usage, and GPU utilization while building robust evaluation suites and documenting tradeoffs for sustainability and impact.

Qualifications

• Solid Python and PyTorch fundamentals.
• Understanding of speech and ASR basics.
• Experience with model training, fine-tuning, and evaluation.
• Familiarity with GPU inference and optimisation workflows.
• Practical ML engineering mindset, not just theory.

Responsibilities

• Experiment with and tune speech/ASR models for SEA languages and accents.
• Design and run experiments under realistic production constraints (latency, cost, memory).
• Work on inference optimisation and GPU utilisation.
• Develop strategies for multilingual and code-switching scenarios.
• Collaborate with engineering to integrate models into production pipelines.
• Build evaluation suites and datasets for tracking model performance.
• Document approaches, experiments, and tradeoffs.

Skills

Python

PyTorch

Speech/ASR

GPU inference

Production ML

Latency optimization

English communication

Education

Bachelor's degree in CS/SE

Tools

Git

Docker

CUDA

Kubernetes

Job description

VALSEA is seeking an applied ML engineer to own end-to-end improvements in speech and ASR under real production constraints in Singapore. You will push models from experiments into deployed systems, focusing on multilingual and code-switching scenarios with diverse data and latency/cost limits.

You will collaborate with engineers to optimize inference, memory usage, and GPU utilization while building robust evaluation suites and documenting tradeoffs for sustainability and impact.