Staff Machine Learning Engineer

About the role

Bjak is building proactive, AI-native applications to assist users with daily tasks, organization, and workflows without the need for complex prompting. As a Staff Machine Learning Engineer, you will lead the execution layer of the company's intelligence, transforming research and model capabilities into reliable, scalable production systems. This role involves managing the entire model lifecycle, including data, training, evaluation, inference, and deployment.

Responsibilities

• Own the end-to-end ML systems powering the company, from data and training to evaluation, inference, and deployment.
• Build and evolve training and fine-tuning pipelines for large models.
• Design evaluation systems that measure capability, robustness, safety, and real-world product performance.
• Architect high-performance inference systems, optimizing latency, GPU utilization, memory, cost, and reliability.
• Build data pipelines and systems for high-quality real-world and synthetic training data.
• Establish reliable production infrastructure for deploying, monitoring, and continuously improving models.
• Partner closely with research and application engineering to turn model capabilities into product improvements.
• Make pragmatic technical trade-offs and rapidly iterate based on real-world performance.

Required skills

• Python
• PyTorch
• JAX
• ML systems
• Large-model training
• Fine-tuning
• Inference
• Software engineering
• GPU-based systems

About the Company

Bjak is a small, high-talent-density team focused on building proactive applications for billions of users. They prioritize speed, engineering fundamentals, and broad ownership, aiming to bring practical AI benefits to global users.