Technical Lead, Machine Learning

📋 Description

• Design, build, and scale production ML systems for AI apps.
• Own infra to train, deploy, monitor, and optimize LLMs in production.
• Develop and maintain training pipelines, evaluation frameworks, and data workflows.
• Fine-tune foundation models using LoRA, QLoRA, SFT, and DPO.
• Optimize model inference performance, latency, reliability, and GPU utilization.
• Build high-quality datasets and robust evaluation processes to measure AI capabilities.

🎯 Requirements

• Proven experience building and deploying production ML systems used by real users.
• Strong Python skills; hands-on with PyTorch or JAX.
• Practical experience with large language models: fine-tuning, evaluation, inference optimization.
• Deep understanding of ML infrastructure, distributed training, and GPU computing.
• Strong software engineering mindset focused on scalability, reliability, maintainability, and code quality.
• Experience designing ML pipelines, deployments, monitoring systems, and production AI services.

🎁 Benefits

• Founding engineering role with significant ownership over technical direction and product architecture.
• Opportunity to build AI infrastructure and systems from early development stages.
• Competitive compensation package including cash compensation and equity opportunities.
• Remote-first working environment with flexibility across eligible locations.
• Opportunity to work with a small, highly talented engineering team solving challenging AI problems.
• Strong impact and visibility, with the ability to shape engineering culture and standards.