At a Glance
- Tasks: Build and optimise data ingestion and search systems for our innovative AI products.
- Company: Fastest-growing startup revolutionising the IP industry with elite backing.
- Benefits: Competitive salary, significant equity, full visa sponsorship, and private medical insurance.
- Other info: Join a dynamic team with free meals and excellent career growth opportunities.
- Why this job: Make a real impact on cutting-edge AI technology and work with top-tier experts.
- Qualifications: Strong Python and SQL skills, experience with large datasets and production data pipelines.
The predicted salary is between 63000 - 77000 £ per year.
About Us
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. Backing: Recently featured in Sifted following our $40M Series B announcement, bringing our total funding to $55M from elite investors including Y Combinator, 20VC, Visionaries, Microsoft and Thomson Reuters.
About the role
We’re hiring a data engineer to build the ingestion and search systems behind Solve Intelligence’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
Must haves:
- 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.
Nice to Have:
- 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).
What we offer
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.
Data Engineer in London employer: Solve Intelligence
At Solve Intelligence, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration. As a Patent Litigator in our fast-paced London team, you'll not only have the opportunity to shape cutting-edge litigation strategies but also enjoy significant equity, private medical insurance, and free meals, all while working alongside some of the brightest minds in the industry. Join us on our journey to revolutionise the IP landscape and experience unparalleled growth opportunities in a supportive environment.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer in London
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Solve Intelligence!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Data Engineer at Solve Intelligence.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Solve Intelligence.
✨Apply Directly through Our Website
When you find a suitable opening like Data Engineer at Solve Intelligence, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Data Engineer in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Solve Intelligence, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Solve Intelligence. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Solve Intelligence
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Solve Intelligence!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
