Senior Machine Learning Engineer

K2 PARTNERING SOLUTIONS PTE. LTD.; Singapore; On-site; SGD 180,000 - 300,000; Full time

Job summary

K2 PARTNERING SOLUTIONS PTE. LTD. is seeking a Senior Member of Technical Staff – Machine Learning to drive the development of core ML infrastructure. You will translate ambiguous requirements into practical designs and ship scalable systems to production in a hands-on role.

You will lead end-to-end ML efforts, including data pipelines, model training, inference, and deployment, while mentoring junior engineers and working across Research, Product, and Platform teams.

Qualifications

• Experience shipping and sustaining production ML systems with active user bases.
• Strong mastery of production software engineering practices (modular design, testing, maintainability).
• Deep familiarity with modern deep learning models, optimization techniques, and edge-case behavior.

Responsibilities

• Architect, deploy, and maintain core ML systems powering long-horizon AI features.
• Manage the full ML lifecycle, including data pipelines, model training, evaluation, inference, and continuous deployment.
• Convert experimental research models into production-ready microservices.
• Monitor, debug, and resolve production anomalies within latency, cost, and safety constraints.
• Collaborate with Research, Product, and Platform teams to deliver user-facing value.
• Mentor junior and mid-level ML engineers.

Skills

Production ML

System design

Python

ML ops

Communication

Tools

PyTorch

JAX

Distributed GPUs

CI/CD

Job description

We are seeking a Senior Member of Technical Staff – Machine Learning to drive the development of our core ML infrastructure and subsystems. In this role, you will lead end-to-end execution—from translating ambiguous requirements into practical designs to shipping scalable systems into production. This is a hands-on position requiring deep technical expertise and strong systems-level thinking.

Key Responsibilities

• Architect, deploy, and maintain core ML systems powering long-horizon AI features.

• Manage the full ML lifecycle, including data pipelines, model training, evaluation, inference, and continuous deployment.

• Convert experimental research models into resilient, production-ready microservices.

• Monitor, debug, and resolve complex production anomalies within strict latency, cost, and safety constraints.

• Work cross-functionally with Research, Product, and Platform teams to deliver user-facing value.

• Provide technical guidance, architectural oversight, and mentorship to junior and mid-level ML engineers.

Technologies

Python, PyTorch / JAX, Distributed GPU Training & Inference Workflows.

Qualifications

• Demonstrated experience shipping and sustaining production ML systems with active user bases.

• Strong mastery of production software engineering practices (modular design, testing, maintainability).

• Deep familiarity with modern deep learning models, optimization techniques, and edge-case behavior.

• Self-directed problem solver with excellent communication skills and an iterative approach to development.

Key Performance Indicators (KPIs)

• System Reliability: Production ML services consistently meet or exceed performance, latency, and reliability benchmarks.

• Operational Excellence: Fast resolution of production issues with minimal impact on service availability.

• Business Alignment: ML initiatives deliver measurable improvements to core product metrics and business objectives.

• Engineering Quality: Raised team standards through rigorous code reviews and impactful mentorship.