3 months ago
Indonesia (city not specified)Staff+
Responsibilities
- Own end-to-end machine learning systems spanning data, training, evaluation, inference, and deployment.
- Build and evolve training and fine-tuning pipelines for large models.
- Design evaluation systems covering capability, robustness, safety, and real-world product performance.
- Architect and optimize high-performance inference systems for latency, GPU utilization, memory, cost, and reliability.
- Build data pipelines and systems for real-world and synthetic training data.
- Establish production infrastructure for deploying, monitoring, and continuously improving models.
- Partner with research and application engineering to turn model capabilities into product improvements.
- Make technical trade-offs, iterate based on measured performance, and support team delivery.
Requirements
- Experience building and shipping production ML systems used by real users rather than research prototypes or demos.
- Strong understanding of large-model training, fine-tuning, evaluation, and inference.
- Strong software engineering and systems fundamentals with production-grade coding ability.
- Experience operating meaningful-scale, GPU-based ML workloads.
- Comfort understanding large-model failure modes and maintaining correctness, reliability, and production quality.
- Ability to navigate ambiguous problems independently and apply strong technical judgment.
- Bias toward experimentation, measurement, and shipping.
Benefits
- Small, high-talent-density, hands-on team with broad engineering ownership.
- Fast decision-making, close collaboration, and limited process overhead.
- Interviews are conducted through virtual meetings and/or onsite sessions, with three and no more than four interviews.
- Prompt hiring decisions are expected after the interview process.
Categories
About Bjak
Bjak builds an online insurance marketplace for consumers in Malaysia and Southeast Asia, enabling comparison and purchase of car, health, life, and travel policies. Its business model is aggregator-based, earning commissions and fees from insurers and partners while streamlining digital applications and renewals. Founded in 2019 and headquartered in Selangor, it is privately held and is expanding from insurance comparison into broader fintech services via a planned finance super app.