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Machine learning research engineer

Cambridge
Latinx in AI (LXAI)
Research engineer
Posted: 21h ago
Offer description

Overview

Machine Learning Research Engineer role at Latinx in AI (LXAI).

This is a fantastic opportunity to join a market-leading UK AI company, Luminance. Named in Tech Nation’s Future Fifty list and recipient of two Queen’s Awards, Luminance is described as a world-leading AI technology disrupting the legal profession. The role is based in Cambridge, United Kingdom, and is full-time and on-site.


Responsibilities

* Join a small, dynamic R&D team to prototype, build, and implement new approaches to AI problems.
* Determine output quality, efficiency, and feasibility in a data-driven manner compared with other techniques.
* Collaborate with team members on research activities and contribute to the advancement of AI solutions.


Qualifications & Requirements

* Strong analytical skills and ability to approach tasks in a scientific manner.
* Data science skills, including handling of large data sets, modelling, and evaluation.
* Understanding of software engineering concepts, particularly with machine learning development.
* Experience with machine learning Python frameworks such as PyTorch, TensorFlow and Scikit-Learn.
* For more senior candidates: understanding of, including published work within, related academic fields such as NLP, Computer Vision or Deep Learning.
* Relevant industry experience with demonstrable impact in a commercial setting.
* Significant practical usage of modern ML areas (NLP, Transformers, LLMs, NER, GANs, Reinforcement Learning, etc.).
* Master’s degree or postgraduate qualification from a top 200 global university, preferably in a technical subject (preferred).


Location & Employment

* Location: Cambridge, England, United Kingdom.
* Employment type: Full-time.
* Seniority level: Entry level (and open to more senior candidates with demonstrated experience).

Note: This description reflects the information provided in the job posting and has been refined for clarity and formatting. All content is kept in the original language and context as given.

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