Who are Picnic & what do we do?
Picnic's mission is to
drive a higher quality ad-funded internet. With 70% of people finding digital ads annoying, brands are wasting ad spend on ineffective and potentially damaging ad experiences. We're a fast-growing, founder-led start-up, passionate about making digital ads work better for everyone.
Now, we're looking for our first ever
Applied Machine Learning Engineer to help us build intelligent systems that power the future of digital advertising.
Requirements
What will you be doing as an Applied Machine Learning Engineer?
- Build applied ML systems that make our product smarter and more defensible
- Develop contextual categorisation of web content (e.g. automatically recognising industry categories)
- Prototype algorithms that can improve advertising outcomes, such as smarter bidding or optimisation logic
- Work closely with product and commercial teams to package outputs into demos and case studies for clients
- Collaborate with engineers to integrate ML features into production system
- Establish good practices for applied ML in the business, bringing your curiosity and drive to help us move fast while building robust foundations
- Apply modern LLM techniques to business problems:
- Use prompt-engineering strategies to get consistent, accurate results
- Explore augmentation methods (e.g. combining LLMs with our own data via embeddings or retrieval)
- Run fine-tuning experiments to adapt general models to our specific domain
Who are we looking for?
We're looking for someone who is curious, hands-on and eager to shape the future of Machine Learning at Picnic. You'll be motivated by solving real world problems with cutting edge techniques and excited about working in a start-up where you'll have a big impact from
day one!
- Ideally, you've got 1-3 years experience in applied ML/AI (or equivalent practical experience through academic projects or early career roles)
- You're comfortable coding in Python and using ML frameworks (e.g. PyTorch, Hugging Face, scikit-learn)
- You've worked with large language models (LLMs) - not just calling APIs, but experimenting with different ways to get the best out of them:
- Prompt engineering (designing effective prompts, chaining prompts)
- Fine-tuning or instruction tuning models for specific tasks
- Embedding-based augmentation (using vector search to give LLMs access to external knowledge)
- Retrieval-Augmented Generation (RAG) or similar techniques
- You've taken messy, real-world data and turned it into useful, structured outputs
- You can show how your work had impact - whether that's a model in production, a working prototype, or an experiment that unlocked a new direction
- You're a clear communicator, able to work across functions with product managers, engineers, and commercial stakeholders
- You're excited by the prospect of being our first ML engineer, owning this area from day one and growing into a lead role quickly
- You don't need to have worked in adtech before - but if you have, that's a bonus!
Benefits
Why will you want to work for Picnic?
You'll be part of a culture that's grounded in our values and pushes us forward every day:
- You're trusted to take ownership, make decisions and deliver with autonomy
- Ideas move quickly from concept to reality - we learn by doing, not over-polishing
- We constantly push ourselves and the industry forward, aiming higher with every piece of work
Together, these values guide us as we tackle hard problems, learn fast and make digital ads better
What can Picnic offer you?
We're proud to have been recognised by
Culture100 and
Flexa as one of the best and most flexible small businesses to work for. We offer:
- A flexible, hybrid working setup (we're usually in the office a few times a week, so being within reach of London Bridge is important)
- 33 days holiday (inclusive of Bank Holidays), plus additional Christmas shutdown
- Private Medical Insurance through Vitality
- Picnic Pension Contribution
- Inclusive Parental Leave Policy
- A great co-working space, regular socials & offsites, Picnic Thursdays, Summer Fridays and Work from Roam opportunities
