Technical Lead, Machine Learning (AI)

Location: Remote, Indonesia

Company

hirify.global is building proactive AI-native applications that help users manage conversations, errands, organization, and workflows with minimal prompting.

What you will do

• Own end-to-end ML 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 high-performance inference systems, optimizing latency, GPU utilization, memory, cost, and reliability.
• Build high-quality real-world and synthetic data pipelines and production infrastructure for model deployment and monitoring.
• Partner with research and application engineering to turn model capabilities into product improvements and make pragmatic technical trade-offs.

Requirements

• Experience building and shipping production ML systems used by real users.
• Strong understanding of large-model training, fine-tuning, evaluation, and inference.
• Strong software engineering and systems fundamentals, with production-grade coding practices.
• Experience operating ML workloads at meaningful scale, particularly GPU-based training and inference systems.
• Ability to navigate ambiguous problems independently and prioritize experimentation, measurement, correctness, and reliability.
• Proficiency with Python and PyTorch or JAX.

Nice to have

• Experience understanding failure modes of large models and translating research into production-ready solutions.

Culture & Benefits

• Small, high-talent-density, hands-on team with broad engineering ownership.
• Fast decision-making and close collaboration with minimal process overhead.
• Emphasis on independent execution, strong technical judgment, and balancing speed with engineering fundamentals.
• Virtual and/or onsite interviews with a target of three and no more than four interviews.
• Prompt decisions following technical team evaluation.

Hiring process

• Applications are evaluated by technical team members.
• Interviews are conducted via virtual meetings and/or onsite.
• Expect a prompt hiring decision after the interview process.