Founding Machine Learning Engineer

17 hours ago

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BJAK

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eCommerce • Insurance • Marketplace

BJAK is a leading online platform in Southeast Asia that offers comprehensive automobile insurance comparison services. The company enables Malaysian users to compare and purchase auto insurance from multiple insurers efficiently, providing considerable savings and convenience. BJAK is renowned for its user-friendly digital platform that allows quick insurance and road tax renewals, offering discounts up to 11%. With a strong emphasis on customer service, BJAK also provides 24/7 roadside assistance, accident support, and replacement vehicles. It is a pioneer in the insurance comparison sector in the region and has facilitated significant savings for millions of car owners.

51 - 200 employees

🛍️ eCommerce

🏪 Marketplace

📋 Description

• Build end-to-end training pipelines: data → training → eval → inference • Design new model architectures or adapt open-source frontier models • Fine-tune models using state-of-the-art methods (LoRA/QLoRA, SFT, DPO, distillation) • Architect scalable inference systems using vLLM / TensorRT-LLM / DeepSpeed • Build data systems for high-quality synthetic and real-world training data • Develop alignment, safety, and guardrail strategies • Design evaluation frameworks across performance, robustness, safety, and bias • Own deployment: GPU optimization, latency reduction, scaling policies • Shape early product direction, experiment with new use cases, and build AI-powered experiences from zero • Explore frontier techniques: retrieval-augmented training, mixture-of-experts, distillation, multi-agent orchestration, multimodal models

🎯 Requirements

• Strong background in deep learning and transformer architectures • Hands-on experience training or fine-tuning large models (LLMs or vision models) • Proficiency with PyTorch, JAX, or TensorFlow • Experience with distributed training frameworks (DeepSpeed, FSDP, Megatron, ZeRO, Ray) • Strong software engineering skills — writing robust, production-grade systems • Experience with GPU optimization: memory efficiency, quantization, mixed precision • Comfortable owning ambiguous, zero-to-one technical problems end-to-end • Nice to Have: Experience with LLM inference frameworks (vLLM, TensorRT-LLM, FasterTransformer) • Contributions to open-source ML libraries • Background in scientific computing, compilers, or GPU kernels • Experience with RLHF pipelines (PPO, DPO, ORPO) • Experience training or deploying multimodal or diffusion models • Experience in large-scale data processing (Apache Arrow, Spark, Ray) • Prior work in a research lab (Google Brain, DeepMind, FAIR, Anthropic, OpenAI)

🏖️ Benefits

• Extreme ownership and autonomy from day one - you define and build key model systems. • Founding-level influence over technical direction, model architecture, and product strategy. • Remote-first flexibility • High-impact scope—your work becomes core infrastructure of a global consumer AI product. • Competitive compensation and performance-based bonuses • Backing of a profitable US$2B group, with the speed of a startup • Insurance coverage, flexible time off, and global travel insurance • Opportunity to shape a new global AI product from zero • A small, senior, high-performance team where you collaborate directly with founders and influence every major decision.