Machine Learning Engineer / Technical Lead

📋 Description

• Build end-to-end ML systems: data pipelines, training, evaluation, inference, deployment.
• Fine-tune large models (LoRA, QLoRA, SFT, DPO, distillation).
• Architect scalable inference systems balancing latency, cost, reliability.
• Design and maintain data systems for synthetic and real-world training data.
• Implement evaluation pipelines for performance, robustness, safety, and bias.
• Own production deployment: GPU optimization, memory efficiency, latency reduction.

🎯 Requirements

• Proficient in Python; experience with PyTorch and/or JAX.
• Experience building production ML systems and end-to-end ML pipelines.
• Hands-on with fine-tuning large language models: LoRA, QLoRA, SFT, DPO.
• Expertise in GPU-based training and inference optimization.
• Strong systems design and data engineering for synthetic and real-world data.
• Collaborative with cross-functional teams (backend, mobile, desktop).