Senior AI Engineer

Business Unit Intro

Our team of 200 colleagues is at the heart of The Economist Group’s digital-first agenda. Together, we are delivering user-friendly, high-quality digital products that bring data, intelligence and analysis to our growing global audiences across all our four businesses.

Our team develops cutting-edge products that provide valuable insights and analysis to business and government leaders worldwide. Whether it involves creating new products for the Economist Intelligence Unit (EIU), conceptualising mobile applications that deliver personalised content, or enhancing our flagship website, economist.com, the Technology team plays a crucial role in shaping how we attract, convert, engage, and retain our 1.2 million subscribers.

The Technology team collaborates closely with other teams to engineer innovative solutions that cater to the evolving needs of our subscribers. This includes leveraging advanced technologies and methodologies to enhance the acquisition of new subscribers, optimise conversion rates, deliver engaging user experiences, and ensure long-term subscriber loyalty.

Job Description

The role:

We are looking for a 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 relevant architecture of our Economist.com and EIU 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 a mid-level NLP Engineer, or even an AI or 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 serverless functions, Airflow, MLflow, or other.
• Working with Data Engineers and 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, prompt engineering, 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.
• Participate in designing and building NLP pipelining and choosing data processing techniques, which make it easier for them to integrate and consume data needed for various 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.

What we’re looking for:

• 4+ years of professional experience with NLP used in large scale digital applications.
• Extensive experience with programming in Python and Jupyter notebooks.
• Professional experience of designing, building and managing bespoke NLP solutions in cloud environments.
• Experience in building NLP solutions while consuming LLMs, either directly from third party APIs or directly from repositories such as Hugging Face.
• Fundamental technical expertise in cloud-native technologies, such as AWS Lambda, API Gateway, SageMaker Studio, Amazon ECR, Cloud Formation, or equivalent.
• Experience in leading / mentoring NLP / ML engineering teams.
• Familiarity in working in teams with data scientists and data engineers, for building automated pipelines for model building, deployment and monitoring.
• An advanced degree in computer science, information science, data science, linguistics, or a related quantitative field or equivalent work experience.
• Strong verbal and written communication skills and ability to work well with a wide range of stakeholders.
• Strong ownership, scrappy and biassed for action.

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