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Technical Lead, Machine LearningBjak • GB
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Technical Lead, Machine Learning

Technical Lead, Machine Learning

Bjak • GB
30+ days ago
Job type
  • Full-time
Job description

About the Role

A1 is building a proactive AI chat app for everyday users to bring intelligence to conversations, errands, organising and workflows. Unlike traditional chat-based applications, our product focuses on achieving high reliability for long-running workflows, persistent context, and real-world task completion. The system must handle multi-step reasoning, interact with external tools, and remain reliable despite non-deterministic model behavior.

As Technical Lead, Machine Learning, you own the execution layer of A1’s intelligence. You translate research direction into reliable, scalable, production-grade ML systems.

This role sits at the intersection of research, infrastructure, and product. You are responsible for making models trainable, deployable, observable, and performant under real-world constraints.

What You'll 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 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.
  • Implement evaluation pipelines covering performance, robustness, safety, and bias, in partnership with research leadership.
  • Own production deployment, including GPU optimization, memory efficiency, latency reduction, and scaling policies.
  • Collaborate closely with application engineering to integrate ML systems cleanly into backend, mobile, and desktop products.
  • Make pragmatic trade-offs and ship improvements quickly, learning from real usage.
  • Work under real production constraints: latency, cost, reliability, and safety

Outcomes

  • Research and models reliably translate into production-ready solutions with clear performance and quality targets.
  • ML pipelines, training loops, and inference systems are stable, efficient, and maintainable.
  • Production issues are detected, debugged, and resolved quickly, minimizing user impact.
  • Team members are supported, aligned, and able to deliver high-impact ML work with minimal friction.
  • Iterations on models and systems are measurable, safe, and improve user experience over time.

Tech Stack

  • Python
  • PyTorch / JAX
  • GPU-based training and inference system

Ideal Experience

  • You have built or shipped real ML systems used by people, not just demos.
  • You are comfortable working with large models and understanding their failure modes.
  • You write strong, production-grade code and care about system correctness.
  • You are self-directed, pragmatic, and take full ownership of outcomes.
  • You communicate clearly and collaborate well in small, high-trust teams.
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Technical Lead, Machine Learning • GB

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