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11 checksActively hiring
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- Still on the company's own careers site, checked 3 h agoModerate evidence
- A hiring contact is attached to itSlight evidence
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Data Engineer
- Office
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Sign Up to ReadDescription
We're the fastest-growing startup transforming the IP industry.
Traction: 20-30% MoM revenue growth; selling to 700+ global IP teams (DLA Piper, tech boutiques, and global enterprises).
Proven Value: Users report 50-90% efficiency gains using our AI platform.
About the role
We’re hiring a data engineer to build the ingestion and search systems behind the company’s AI products.
Our sources include global patent literature, case law, technical standards and contributions, scientific databases, academic papers, and content from across the web. The data spans structured records, documents, images, audio and video. You’ll work across bulk ingestion and on-demand retrieval, making this information searchable and useful in our products
You’ll own systems from source acquisition through to serving queries. The work includes:
Large-scale ingestion. Build and operate high-throughput, resumable pipelines for large datasets, with efficient incremental updates, monitoring and recovery from failures.
Document processing and data quality. Extract useful content from complex documents and other formats. Handle malformed records and changing schemas, and validate outputs while preserving structure and metadata.
Search and serving. Build keyword, vector and structured search, and design schemas, indexes and partitioning for fast queries over tens to hundreds of millions of records.
Connecting information across sources. Link patents, scientific records and supporting documents, preserve dates and versions, and make results traceable to their original sources.
Performance engineering. Profile parsing, ingestion, database builds and queries throughout development, testing against representative datasets at realistic scale. Diagnose CPU, memory and storage I/O bottlenecks, and tune jobs and infrastructure for throughput, latency and cost.
You’ll work closely with our AI researchers and product engineers, with substantial freedom to choose the approach and build the systems yourself.
What you bring
Requirements
- Strong Python and SQL, with experience designing and operating production databases.
- Solid experience building and operating production data pipelines over large, messy datasets.
- Expertise with running search systems over large document collections.
- End-to-end ownership from raw data to user-facing functionality.
- A good understanding of schema design, indexing and query optimisation.
- A track record of diagnosing and fixing performance bottlenecks in live systems through profiling and measurement.
- Experience with PostgreSQL/pgvector, OpenSearch (or Elasticsearch), Spark/Delta Lake, AWS, NoSQL databases, or Rust/C++ is useful.
- The Founders
- You'll partner with a founding team of AI PhDs and elite systems engineers:
- Sanj (CRO): PhD in AI (Gatsby Unit, UCL), ex-Huawei R&D, former lead at Magic Carpet AI (acquired).
- Chris (CEO): PhD in AI (UCL), published researcher, ex-Dyson and Alan Turing Institute.
- Angus (CTO): MEng Computer Science, ex-Qualcomm and Coremont (Brevan Howard).
Benefits
- Competitive Salary + Significant Equity: We want you to have true ownership in the success of the company.
- Founding Impact: You'll have a direct hand in how we build out the data infrastructure the rest of the product depends on.
- Support: Full visa sponsorship and private medical insurance.
- The Environment: Free meals and a seat at the table with an incredibly smart, ambitious team.
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- Experience: Any (new grads ok)
- Visa: US citizen/visa only
Where you’d work
From the office
The office
- London, United KingdomMap for London, United Kingdom (opens in a new tab)
No visa sponsorship
About the company
Company hidden
Office in London, United Kingdom
Fair
Your chances
Still hiring, moderately crowded, and a person reads your message.
- 16 checks run
- 4 good signs
- 1 red flag
How crowded?
5 checksModerate
In its favour2
- You can message the hiring contact and skip the queueModerate evidence
- In the office in London: only people nearby can take itSlight evidence
Against it1
- Open for 2 weeks: applications have had time to pile upModerate evidence
Fits Me
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- Must-haves
Details11 facts · Role, Location, Compensation, Employment- Tech stack
- Python
- SQL
- PostgreSQL
- AWS
- Spark
- Vector databases
- Type
- Full-time
- Equity
- Equity offered
- Specialty
- Data Engineering
- Region
- United Kingdom
- Pay period
- Annual
Show 5 more factsShow less
- Python
- SQL
- PostgreSQL
- AWS
- Spark
- Vector databases
Role
- Category
- Data & Analytics
- Specialty
- Data Engineering
- Tech stack
- Python
- SQL
- PostgreSQL
- AWS
- Spark
- Vector databases
Location
- Work model
- Office
- Region
- United Kingdom
- Office
- London, United Kingdom
- Visa sponsorship
- Not sponsored
Compensation
- Salary
- Salary by agreement
- Pay period
- Annual
- Equity
- Equity offered
Employment
- Type
- Full-time
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