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Staff Machine Learning Engineer at NLPatent

London, England, United Kingdom -

Full Time

Start Date

Immediate

Expiry Date

17 May, 26

Salary

0.0

Posted On

16 Feb, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Technical Leadership, Python Programming, Machine Learning, Natural Language Processing, Tensorflow, PyTorch, Search Databases, Elasticsearch, Opensearch, Cloud Service Providers, AWS, Data Pipelines, Search Algorithms, Agentic Workflows, LLMs, NLP

Industry

Software Development

Description

NLPatent is an industry leading AI-first patent research platform that was an early mover in the application of Large Language Models. We use a combination of proprietary and off-the-shelf machine learning models and NLP techniques to help our users answer patent related research questions such as "Is my invention patentable?". Increasingly, we're using generative LLMs to build agentic workflows that answer research questions without any human intervention. As a staff level applied scientist at NLPatent, you'll be the technical lead for all data and NLP related work at NLPatent. You'll be responsible for improving search performance (precision and recall), optimizing search algorithms to ensure quick results, designing and implementing agentic workflows, building and maintaining data pipelines, and much more. 8+ years of commercial engineering and data science experience Experience with technical leadership Extensive experience with Python programming Commercial Machine Learning experience Experience working in Natural Language Processing (NLP) Experience training machine learning models using Tensorflow and PyTorch Experience working with search databases (e.g. Elasticsearch, Opensearch, etc.) Experience with cloud service providers (e.g. AWS) Willing to work 3 days per week onsite in the office in London Stock Option Plan 25 days holiday allowance Pension contributions Flexible Working Training & Development

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Responsibilities

The Staff Machine Learning Engineer will serve as the technical lead for all data and NLP initiatives, focusing on improving search performance, optimizing algorithms for speed, and designing and implementing generative LLM-based agentic workflows. Responsibilities also include building and maintaining necessary data pipelines to support these advanced research applications.