About Us
Here at the Financial Times, gold-standard journalism is just the beginning. 500+-people strong, our Product & Tech team keeps us ahead of the ever-changing digital landscape by delivering cutting-edge products to over one million digital subscribers every day. Our plans for growth rely on a diverse, dedicated and dynamic group of product, tech, delivery and data specialists - everyone’s welcome in this friendly, forward-thinking team. And with entrepreneurial spirit, intelligence and opportunity at every turn, there’s no limit to where your FT career will take you.
Role & Team Overview
The Accelerate AI team is being formed. The team pulls together the diverse knowledge and skills from our product, tech and data teams to move fast in both experimenting and developing full end-to-end products. This team is dedicated to speeding up the development and implementation of generative AI products at FT.
The first challenge the team is taking on is enabling the newsroom to create more value through summarisation and story finding, e.g. telling stories that we wouldn't have otherwise. The scope will also include developing strategies for new channels and consumption behaviours, and audience-facing products.
The MLOps engineer role will also be part of a 4-strong MLOps team that are growing.
Our Tech Stack
We Often Use These, It's Not An Exhaustive List But Gives You a Taste Of What Our Technology Stack And Tools Look Like
- Python, R
- SQL, knowledge graph, SingleStore, BigQuery
- Machine Learning platforms like Posit/RStudio
- GitHub, CircleCI
- AWS: ECS/EKS, CloudFormation, Redshift
- Kubernetes: Helm charts, kubectl, eksctl
- Streaming technologies like Kafka, Spark, or Flink
- GPU technologies
- Splunk, Prometheus, Graphite, Grafana
What You'll Be Doing
- Champion, instаll, and develop frameworks for software engineering best practices within NLP and Machine Learning for content use cases
- Support the GenAI Accelerate team and the Data Scientist(s) in that team with building, documenting and testing machine learning pipelines in line with FT Data Science Team process and best practice
- Work collaboratively with Data Scientists, Data engineers and Product managers to deploy and operate systems
- Design and implement low maintenance, well monitored, secure and scalable solutions to the problems the GenAI Accelerate team is solving
- Being able to establish and be a promoter of good coding and engineering practices for NLP and ML within GenAI Accelerate team
- Contribute to company-wide processes, frameworks and guidelines
- Develop an in-depth understanding of FT’s underlying data and data flow, data structures.
- Supporting engineering product support on new capabilities and enhancements, such as custom Search APIs
What we are looking for
Essential
- Experience productionizing Machine learning algorithms or Data science models
- Experience with containerization, scaling and load balancing, specifically for ML models.
- Experience designing and developing RESTful APIs
- Highly proficient in the programming languages relevant to the Data and Content Analytics domain at the FT - Python and Java
- Experience in developing end-to-end (Data/Dev/ML)Ops pipelines based on in-depth understanding of cloud platforms, AI lifecycle, and business problems to ensure analytics solutions are delivered efficiently, predictably, and sustainably.
Desirable
- Experience with streaming applications such as Kafka streams, Spark streaming
- Experience in modern database technologies (AWS/cloud-based/in-memory etc.), scripting languages, big data technologies
- Experience with Kubernetes
- Experience developing monitoring and maintenance systems for ML models, specifically those based on text data using NLP technologies
- Experience developing cutting edge search capabilities using the latest technologies in semantic search
- Good understanding of the principles and trade-offs of a microservices architecture
- Experience in working with ETL frameworks (job orchestration tools) such as Airflow or Luigi