Senior Machine Learning Engineer

Role Summary

Location:

Flexible

Reports to:

Chief Engineer

Job type:

Full-time, Fixed term

About the Company

Metacognition is a neolab building the future of intelligent agents. We believe that these next agents will be able to update their memory on the fly for years or decades. Metacognition brings together leading researchers who have been at the forefront of developing the key tools needed for long-term memory such as continual learning, LLM adaptation and explicit knowledge representation.

The company has raised in a pre-seed round and we are now hiring across a range of technical roles as we scale our team and reach a number of inflection points in AI performance. If you want to work on some of the hardest and most interesting problems in AI, we want to hear from you.

Role Overview

This role sits within our Engineering / Products team, bridging research and production. The Senior Machine Learning Engineer takes experimental research code and turns it into reliable, efficient, scalable systems, working closely with research scientists and the broader engineering organisation. Role scope will be calibrated to the experience and profile of the candidate.

Key Responsibilities

Engineering

  • Implement, optimise, and scale machine learning models and training pipelines.
  • Build robust data, simulation, and evaluation infrastructure.
  • Bridge research and production — taking experimental code to reliable, efficient systems.
  • Profile and optimise model performance across compute environments.
  • Develop and maintain early-stage demonstrators of research ideas.

Requirements

Essential

  • Strong Python skills.
  • Hands-on experience training and deploying deep learning models on cloud infrastructure.
  • Familiarity with PyTorch or JAX.
  • Genuine intellectual curiosity, collaborative mindset, and comfort working in a fast-paced research environment.

Preferred

  • Experience with large-scale model training (LLMs, vision-language models, or similar).
  • Familiarity with simulation environments, synthetic data generation, or evaluation pipelines.
  • Prior experience in a research lab, deep tech company, or AI-focused startup.
  • Track record of shipping research or products in a collaborative team setting.