🛠 Tech Stack

💼 About This Role

You'll build and own end-to-end ML pipelines for a proactive AI system that understands context across conversations. You'll turn research into production-grade ML systems and own the execution layer of A1's intelligence. This role offers the chance to ship quickly and learn from real usage under production constraints.

🎯 What You'll Do

• Build and own end-to-end ML pipelines spanning data, training, evaluation, inference, and deployment.
• Fine-tune and adapt models using methods such as LoRA, QLoRA, SFT, DPO, and distillation.
• Architect and operate scalable inference systems, balancing latency, cost, and reliability.
• Design and maintain data systems for high-quality synthetic and real-world training data.

📋 Requirements

• Strong background in deep learning and transformer-based architectures.
• Hands-on experience training, fine-tuning, or deploying large-scale ML models in production.
• Proficiency with at least one modern ML framework (e.g. PyTorch, JAX).
• Experience with distributed training and inference frameworks (e.g. DeepSpeed, FSDP, Megatron, ZeRO, Ray).

✨ Nice to Have

• Experience with LLM inference frameworks such as vLLM, TensorRT-LLM, or FasterTransformer.
• Contributions to open-source ML or systems libraries.
• Background in scientific computing, compilers, or GPU kernels.

🎁 Benefits & Perks

• 🚀 High talent density team – work with world-class peers.
• ⚡ Rapid iteration – ship quickly and learn from real usage.
• 🌍 Remote work – flexibility to work from anywhere.
• 🎯 Ownership – own end-to-end ML systems from zero to one.

📨 Hiring Process

If there appears to be a fit, we'll reach out to schedule 3-4 interviews, conducted virtually or onsite, with a prompt decision.

🚩 Heads Up

• Principal-level role requiring 'a bias toward shipping' and 'learning fast' which may indicate high pressure.
• No explicit years of experience required, but 'strong background' and 'hands-on experience' are vague.
• Zero-to-one systems ownership may involve ambiguous expectations.