Staff Machine Learning Engineer (AI)

TL;DR

Staff Machine Learning Engineer (AI): Own end-to-end ML system execution for a proactive AI chat app with an accent on reliable, scalable production-grade systems handling multi-step reasoning and real-world tasks. Focus on fine-tuning models with LoRA/QLoRA/SFT/DPO, architecting inference systems, and ensuring performance under latency, cost, and reliability constraints.

Location: Remote (United Kingdom)

Company

Building a proactive AI chat app for everyday users, focusing on high reliability for long-running workflows, persistent context, and real-world task completion.

What you will do

• Own end-to-end ML system execution: data pipelines, training workflows, evaluation systems, inference architecture, and deployment.
• Fine-tune and adapt models using state-of-the-art methods like LoRA, QLoRA, SFT, DPO, and distillation.
• Architect scalable inference systems balancing latency, cost, and reliability, with GPU optimization and scaling policies.
• Design data systems for high-quality synthetic and real-world training data.
• Implement evaluation pipelines for performance, robustness, safety, and bias.
• Collaborate with application engineering to integrate ML systems into backend, mobile, and desktop products.

Requirements

• Built or shipped real ML systems used by people, not just demos.
• Comfortable with large models and their failure modes.
• Strong production-grade code with focus on system correctness.
• Self-directed, pragmatic, full ownership of outcomes.
• Clear communication and collaboration in small, high-trust teams.

Culture & Benefits

• Small, world-class, high-talent-density team.
• Collective decision-making, rapid speed, balance between quality and learning.
• Hands-on execution with structure, judgment, and independence.

Hiring process

• Applications evaluated by technical team.
• 3-4 interviews via virtual meetings and/or onsite.
• Prompt decision with transparency and efficiency.