At Synthesio, we transform 80 million daily social posts into actionable insights for global brands like Michelin, Renault, Sanofi, and many others, thanks to our real-time AI stack.
We, Ipsos Synthesio, are a leading marketing SaaS company. Our technology allows global brands to make business decisions based on online consumer feedback. We centralize public data from many providers, such as posts on social networks, press articles, forums, search data and more. After the collection phase, we enrich it through AI models and provide intelligence in many visualizations and APIs.
You want to join a deep tech and growing company with at-scale generative artificial intelligence applications, we are hiring candidates!
Lastly, at Synthesio, we have a strong tech culture. This means the teams have an important role. Each squad is empowered, owns together the success of the projects, and chooses their deliverables and their timelines.
Our department
The Synthesio product engineering department is focused on data provisioning, enrichment, and exploitation.
Synthesio crawls numerous public consumer data footprints including social, reviews and ratings, survey, search, and press data, representing more than 80M new documents per day. Each document is then analyzed and enriched using custom NLP and image recognition models developed by our data scientists. All this data is stored in databases and can be accessed by our customers via our dashboarding solution or our APIs.
Job Description
As a member of the back-end team, you will:
Be a full-time member of a squad
Maintain processing pipelines of 80 M documents ingested per day and 100 billion in storage
Design solutions for squad projects, in collaboration with the product owner and the other back-end/front-end/machine-learning developers of the squad
Develop and implement these projects
Define milestones for project implementation and deployment
Evolve and maintain the tools and libraries shared by the back-end team
Our back-end stack: Go, Python, JS, React, MySQL, Elasticsearch, Cassandra, Kafka, Gitlab, Docker, Ansible.
Our platform uses a microservice architecture containing 200+ microservices, most of them written in Go and using Kafka or HTTP to communicate.
The hardware infrastructure is composed of hundreds of rented bare metal servers running Debian. A big part of it is dedicated to storage, including:
1 PB+ Elasticsearch, 750TB+ MySQL clusters, 150 TB+ Scylla DB, and 250TB+ of Kafka.
Example projects we’ve worked on:
Add vector search capabilities.
Data usage tracking to enable cost monitoring and tailored billing.
Implement new crawlers to retrieve documents from more diverse sources.
Revamp of the alerting system for increased stability and additional functionalities.
Custom AI enrichments for clients to further personalize their experience and usage.
