Senior NLP Engineer

at  The Economist Group LTD

Introduction:
Job Title:
Senior NLP Engineer
Business Unit:
Technology / Engineering
Location:
London
Direct Reports:
0
Reporting Manager Title:
Bogdan Vrusias
Date Prepared:
01 / 05 / 2024

WHO WE ARE

We are an organisation that exists to drive progress. That’s the “red thread” that connects everyone at The Economist Group (TEG). Our businesses share a devotion to innovation, independence and rigour in their fields of expertise. We empower people to understand and tackle the critical challenges and changes facing the world. Our analytical rigour, global expertise and evidence-based insights enable individuals and organisations to make sense of these shifts and chart a course through them.
Our story began in 1843, when a Scottish hat manufacturer founded The Economist newspaper to further the cause of free trade. Since then, we have evolved into a staunchly independent global media and information-services company that provides intelligent thinking for an international audience. We deliver our analysis and insights in many formats to subscribers and clients in 170 countries with four businesses, each of which upholds our global reputation for excellence and integrity.

THE ROLE:

We are looking for a Senior Natural Language Processing (NLP) Engineer to join our Economist Group engineering team. Your primary focus will be to design, develop, ship, maintain and oversee the overall architecture of our Economist.com data platforms - with a focus on systems related to our customer facing products. The initial focus will be around implementing appropriate data infrastructure required to enable predictive analytics, ML algorithms, and Generative AI applications, and in conjunction with the Head of AI and Data Engineering support the organisation to implement their vision. You’ll also work with individuals from our corporate data team (responsible for reporting, analytics and insights), as well as work collaboratively with data scientists and analysts in other teams across the organisation.
The role will suit either an existing senior or a mid-level NLP Engineer, or even an ML Engineer ready for their next challenge, but with at least some experience leading or mentoring a high performing team. You should enjoy working with autonomy in a creative and entrepreneurial environment, and have a strong commitment to producing high quality solutions. We offer flexible working and have recently shifted to a ‘remote first’ working policy with a minimum expectation of coming to the office two days a month, however you can come in more often if you wish to.

HOW YOU WILL CONTRIBUTE IN THIS ROLE:

• Architecting, building and maintaining NLP processing pipelines / workflows in Python via technologies such as Spark, serverless functions, Airflow, MLflow, or other.
• Working with Data Scientists to automate experiments that bring ML and NLP research ideas to production.
• Fine Tuning and consuming Large Language Models (LLM) directly or via third party Generative AI API services.
• Setting up Retrieval Augmented Generation (RAG) architectures and Reinforcement Learning from Human Feedback (RLHF) processes.
• Implement MLOps and related DevOps focused on LLMs deployed in cloud-native environments.
• Support, optimise and transition our current processes to ensure well architected implementations and best practices.
• Work in an agile environment within a collaborative agile product team using Kanban
• Collaborate across departments and work closely with data science teams and with business (economists/data) analysts in refining their data requirements for various initiatives and data consumption requirements.
• Educate and train colleagues such as data scientists, analysts, and stakeholders in NLP pipelining and data processing techniques, which make it easier for them to integrate and consume the data they need for their own use cases.
• Participate in ensuring compliance and governance during model use, to ensure that the users and consumers use the resources provisioned to them responsibly through data governance and compliance initiatives.
• Become an NLP evangelist, and promote the available Generative AI capabilities and expertise to business unit leaders, and educate them in leveraging these.