Machine Learning Engineer (LLM)

At Bjak, we’re building AI systems that reach millions across Southeast Asia. Our Machine Learning team is at the forefront of text generation, captioning, moderation, and chat-like interactions, deploying LLMs into real-world products that must be fast, safe, and aligned with our brand voice.
This role is based in Malaysia with a hybrid work arrangement - combining flexible remote work with in-office collaboration at our HQ. You’ll work closely with regional teams across product, engineering, and data to build and scale impactful AI solutions.

We are scaling LLM capabilities that power how people interact with financial services. As a Machine Learning Engineer (LLM), you’ll fine-tune state-of-the-art models, design evaluation frameworks, and bring AI features into production. Your work ensures our models are not only intelligent, but also safe, trustworthy, and impactful at scale.

• Fine-tune & Adapt - Use LoRA/QLoRA to optimize open-source models (LLaMA, Mistral, Gemma) for Bjak’s applications.

• Engineer Prompts & Curate Data - Craft prompts and datasets that reflect tone, brand voice, and safety.

• Evaluate Models – Build metrics pipelines for perplexity, toxicity, and relevance to ensure safe and high-quality outputs.

• Deploy & Monitor – Scale models into production with performance optimization and monitoring for drift.

• Collaborate & Deliver – Partner with product, engineering, and design teams to launch user-facing AI features.

• Treat every problem as your own, regardless of scope or title.

• Enjoy switching hats - builder, debugger, architect, and product thinker when needed.

• Believe clarity comes from action - prototype, test, and iterate without waiting for perfect plans.

• Stay calm and effective in startup chaos - shifting priorities and building from zero doesn’t faze you.

• Bias for speed - you believe it’s better to deliver something valuable now than a perfect version much later.

• See feedback and failure as part of growth - you’re here to level up.

• Believe “done” beats “perfect,” but still care deeply about UX and code quality.

• Show up with humility, hunger, and hustle, and lift others up as you go.

• Strong experience in transformers, deep learning, and fine-tuning methods (LoRA/QLoRA, SFT, distillation).

• Proficiency with PyTorch (preferred) or TensorFlow.

• Skilled in prompt engineering and dataset curation for alignment with tone, safety, and trust.

• Familiar with evaluation metrics: perplexity, toxicity, relevance.

• Strong software engineering foundations in algorithms, data structures, and clean code practices.

• Prior work in text generation, moderation, or personalization.

• Experience with RLHF or reinforcement learning in LLMs.

• Contributions to open-source ML projects.

• Competitive salary and performance-based bonuses

• Flexibility in work arrangement

• High-impact role with visibility across product, data, and engineering

• Flat structure - your work is seen, your ideas are heard

• Fast learning curve and accelerated growth in a mission-driven company

• Cross-border exposure to regional product development

We’re a lean, high-performance team that moves fast and holds a high bar. Titles don’t matter here - output, integrity, and ownership do. Everyone is expected to roll up their sleeves, contribute meaningfully, and take initiative. We reward people who think like owners. We value speed, clarity, and relentless ownership. If you’re hungry to grow and care deeply about excellence, this is your kind of environment.

BJAK is Southeast Asia’s #1 insurance aggregator with 8M+ users, fully owned by its employees. Headquartered in Malaysia and operating in Thailand, Taiwan, and Japan, we help millions of users access transparent and affordable financial protection through Bjak.com. We simplify complex financial products through cutting-edge technologies, including APIs, automation, and AI, to build the next generation of intelligent financial systems.
If you're excited to build real-world AI systems and grow fast in a high-impact environment, we’d love to hear from you.