AI & Automation
Hire Recommendation System Engineers
Recommendation system engineers build the logic that suggests products, content or matches to each user, based on behaviour and item data.
The role
What recommendation system engineers do
A recommendation engineer analyses interaction data, starts with simple baselines like popularity and similarity, builds collaborative or embedding-based models, and tests them with A/B experiments. Handling new users and items with little data is a core challenge.
Typical deliverables
- Recommendation models and ranking logic
- Similar item and personalised suggestions
- Handling for new users and products
- A/B testing setup
- Recommendation APIs
Tools you will see
- Python
- Implicit or LightFM
- Embeddings and vector search
- Feature stores
- Experimentation tools
Choosing
How to choose recommendation system engineers
What to look for
- Simple baselines tested before complex models.
- A/B test results in previous work.
- Solutions for new users and new items.
- Care that recommendations do not just repeat the most popular items.
Questions to ask
- 1What baseline would you start with?
- 2How would you handle new users?
- 3How will we measure whether recommendations help?
- 4What data do you need from us?
Planning
Before you post the job
Enough data?
Personalisation needs interaction data. Small catalogues or low traffic may do better with rules and similarity.
What drives cost
Data preparation, catalogue size, real-time needs, experimentation and serving.
Hiring on Open Lance
- Posting a job and reviewing proposals are free.
- Each milestone is funded into escrow before work starts and paid when you approve it.
- Hire fixed-price, hourly, as a monthly Dedicated Hire, or buy a packaged Drop-In.
- Client fees are shown before you pay and added on top of the work.
FAQ
Questions about hiring recommendation system engineers
Do we need machine learning for recommendations?
Not always. Rules and item similarity can work well, especially early on.
What is the cold start problem?
Recommending for new users or items with little interaction history.
How do we know recommendations work?
Run A/B tests on metrics like clicks, purchases or retention.
Related
Related skills
Post a job for recommendation system engineers
Describe the work and compare proposals. You only fund the first milestone once you have chosen someone.