Senior ML Engineer — Production-Ready AI Systems

ActAI; Singapore; On-site; SGD 120,000 - 200,000; Full time

Job summary

ActAI is seeking a Member of Technical Staff, Machine Learning, to build core ML components and ship production-grade ML systems from day one. You’ll work on real production systems, learning how large-scale ML behaves outside of research settings. The role emphasizes shipping, debugging, and iterating on real-world ML.

You’ll collaborate with senior ML engineers and product teams while contending with latency, cost, reliability, and safety constraints in a production environment.

Qualifications

• Strong foundations in machine learning and modern neural architectures.
• Hands-on experience training, fine-tuning, or deploying ML models.
• Comfortable writing production-quality code and learning new tools quickly.
• Curious, coachable, and eager to learn from real systems in production.
• Able to work through ambiguity with guidance and grow ownership over time.
• Bias toward shipping, iteration, and continuous improvement.

Responsibilities

• Build and improve ML components across data, training, evaluation, and inference.
• Fine-tune and adapt models as part of larger production systems.
• Implement evaluation and testing to understand model behavior.
• Help build and maintain data pipelines for real-world and synthetic data.
• Debug model issues, performance problems, and production incidents.
• Ship improvements iteratively and learn from real user feedback.
• Work closely with senior ML engineers and product teams.
• Work under real production constraints: latency, cost, reliability, and safety.

Skills

Python

Machine Learning

Systems design

Experimentation

Debugging

Tools

PyTorch

JAX

Job description

ActAI is seeking a Member of Technical Staff, Machine Learning, to build core ML components and ship production-grade ML systems from day one. You’ll work on real production systems, learning how large-scale ML behaves outside of research settings. The role emphasizes shipping, debugging, and iterating on real-world ML.

You’ll collaborate with senior ML engineers and product teams while contending with latency, cost, reliability, and safety constraints in a production environment.