At a Glance
- Tasks: Design and build advanced AI retrieval systems that understand complex information.
- Company: Stealthy, early-stage AI company with a focus on foundational technology.
- Benefits: Equity ownership, high autonomy, and the chance to influence core technology.
- Other info: Join a small, dynamic team with minimal bureaucracy and maximum impact.
- Why this job: Work on groundbreaking AI challenges and see your research ideas come to life.
- Qualifications: Experience in information retrieval, NLP, or knowledge representation.
The predicted salary is between 63000 - 77000 £ per year.
What if you could work on the part of AI that sits underneath the application layer? Join a stealth, early-stage AI company building foundational technology for how organisations structure, retrieve and reason over complex information. They’re tackling a problem that becomes increasingly important as organisations adopt AI: having access to more information isn’t enough. The real challenge is understanding relationships, preserving context and being able to reason reliably across large volumes of messy, changing data. We are backed by strong technical talent and are building a small, highly capable team around this problem.
This is an opportunity to work somewhere you can take research ideas, turn them into production systems and have a direct influence on the technical direction of the company.
What you’ll get to work on:
- You’ll design and build retrieval systems that go beyond basic semantic search, combining dense, sparse and structured approaches.
- You’ll explore how information can be represented so that AI systems can reason over entities, relationships and context.
- You’ll build information extraction systems capable of dealing with ambiguous, messy and unstructured data.
- You’ll work on entity recognition, relationship extraction, coreference resolution and temporal understanding.
- You’ll develop approaches for maintaining and evolving knowledge as new information becomes available.
- You’ll work on provenance, validation and conflict resolution so information can be trusted.
- You’ll stay close to relevant research and translate useful ideas into production technology.
- You’ll have significant influence over the architecture and technical direction of these systems.
We’re looking for someone who:
- Has research or industry experience in information retrieval, NLP, knowledge representation, knowledge engineering or a closely related field.
- Has taken research beyond experimentation and into a real-world system.
- Thinks deeply about how information should be structured to support reasoning.
- Understands that retrieval is about more than simply finding the most similar documents.
- Is comfortable working from first principles and defining problems without a predefined roadmap.
- Enjoys working in a small team where you’ll have significant ownership.
- Is pragmatic and cares about shipping useful systems rather than research for research’s sake.
You could come from academia, an applied research team or a highly technical engineering environment. The key thing is the depth of your thinking and your ability to turn that thinking into something that works.
Work on foundational AI problems: Get beyond the application layer and work on how AI systems actually understand and reason over information.
Research → production: See your ideas move from papers and experiments into systems used in the real world.
High ownership: You’ll have genuine responsibility for a core part of the technology.
Small technical team: Work closely with experienced founders and engineers without layers of management.
Technical influence: Your decisions will directly shape the architecture and direction of the platform.
Intellectual challenge: Work on difficult problems around retrieval, knowledge representation and reasoning that don’t have obvious answers.
Equity: Have meaningful ownership in an early-stage company.
The environment: You’ll be joining a small, founder-led and deeply technical team where you’ll be expected to think independently, challenge assumptions and move quickly. There isn’t a huge amount of process or bureaucracy. You’ll have a high degree of autonomy, but you’ll also have a high bar for technical thinking and execution. The team works hybrid from London, with flexibility around how and where you work. The company is currently operating in stealth, so further information about the product and customers will be shared during the interview process.
If you’re interested in NLP, retrieval, knowledge representation or reasoning and want to work on a genuinely foundational AI problem rather than another wrapper around an existing model, I’d be happy to tell you more.
Founding Applied Research Engineer | AI & Knowledge Systems employer: Oho Group
Join a pioneering early-stage AI company in London, where you'll have the unique opportunity to work on foundational technology that shapes how organisations understand and reason over complex information. With a strong emphasis on autonomy and technical influence, you'll be part of a small, highly capable team that values innovative thinking and offers meaningful ownership in the company's success. The collaborative and flexible work culture fosters personal growth and encourages you to turn research ideas into impactful production systems.
StudySmarter Expert Advice🤫
We think this is how you could land Founding Applied Research Engineer | AI & Knowledge Systems
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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 Oho Group.
✨Apply Directly through Our Website
When you find a suitable opening like Founding Applied Research Engineer | AI & Knowledge Systems at Oho Group, 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 Founding Applied Research Engineer | AI & Knowledge Systems
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 Oho Group, 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 Oho Group. 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 Oho Group
✨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 Oho Group!
✨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.
