🛠 Tech Stack

💼 About This Role

You'll build production-grade ML systems for a proactive AI platform. You'll own end-to-end training and inference pipelines that enable context-aware conversations. This role offers hands-on work with cutting-edge models under real-world constraints.

🎯 What You'll Do

• Build and own end-to-end ML pipelines.
• Fine-tune models using LoRA, SFT, DPO.
• Design and maintain data systems for training data.
• Implement evaluation pipelines for performance and safety.
• Optimize GPU memory and inference latency.

📋 Requirements

• Strong background in deep learning and transformer architectures.
• Hands-on experience training or deploying large-scale ML models in production.
• Proficiency with PyTorch or JAX.
• Experience with distributed training frameworks like DeepSpeed or FSDP.

✨ Nice to Have

• Experience with vLLM or TensorRT-LLM.
• Contributions to open-source ML projects.
• Experience with RLHF pipelines (PPO, DPO).

📨 Hiring Process

Estimated timeline: 2-3 weeks · AI estimate

1. 1Technical Phone Screen· 45 min
2. 2Technical Interview· 60 min
3. 3Onsite Interview· 3 hours