Description review
Senior Recommendation Systems Engineer
Matchmatch · Remote - Warsaw · back to the listing
HR standards
60/100
needs work
Title ↔ description
91/100
strong
Reads as
Machine Learning Engineer
99% confident
What this role officially is
data scientist — ESCO, the EU occupation classification
Data scientists find and interpret rich data sources, manage large amounts of data, merge data sources, ensure consistency of data-sets, and create visualisations to aid in understanding data. They build mathematical models using data, present and communicate data insights and findings to specialists and scientists in their team and if required, to a non-expert audience, and recommend ways to apply the data.
Also known as: data scientists, data engineer, research data scientist, data expert, data research scientist
How others title the same work
Large employers
- Applied AI Engineer Automattic
- Machine Learning Engineer, CX Intelligence Coinbase
- AI Engineer - FDE (Forward Deployed Engineer) Databricks
- AI Engineer - FDE (Forward Deployed Engineer) - U.S. Federal Sector Databricks
- Senior AI Engineer – Notebooks Datadog
Startups
- Attendi | Medior Machine Learning Engineer | Amsterdam, Netherlands | ONSITE (hybrid) | €6,000 - €7,000 per month | Full-time (80–100%, ~4–5 days/week) | Visa sponsorship + 30% ruling possible Attendi
- Member of Technical Staff (applied) Anthrogen
- Aptura AI | Full-Time | MTS (Applied AI), MTS (SWE / Product) | London | ONSITE / HYBRID Aptura AI
- Arcforma AI (arcforma.ai) | AI Engineer (Marketing / Construction / Arcforma AI (arcforma.ai)
- Staff AI Engineer - Agent Architecture & Behavior Artisan
What the listing never says
- 22 bullet points. Long requirement lists deter qualified candidates, who read them as hard gates. Scope clarity
- No section describes what the person would actually do. Scope clarity
- No pay range published. Candidates cannot tell whether applying is worth their time. Pay transparency
The listing, marked up
Nothing in the wording of this listing tripped a check. The scores above still judge how complete and coherent it is.
We're hiring for an early-stage, AI-first startup changing how people discover and choose fragrances.
The team is building a product that helps people find scents based on their preferences, emotions, and the experiences they're looking for.
Behind the product are second-time founders with a successful exit and experience at Pinterest. It's a small, talented team building something where search, recommendations, and personalization are at the heart of the user experience.
We're looking for a Recommendation Systems Engineer to take ownership of how the product understands user preferences and recommends fragrances.
You'll work directly with the founders, engineers, and product team to design, build, and improve recommendation systems from the ground up.
What you'll work on
• Design and build personalized recommendation systems, semantic search and similar-fragrance discovery.
• Develop candidate retrieval, ranking and re-ranking approaches.
• Solve cold-start challenges and identify useful user signals.
• Build data pipelines and ML-powered services that support recommendations.
• Define evaluation metrics, run experiments and measure recommendation quality.
• Make practical architecture decisions and take systems from idea to production.
• Contribute to backend and product engineering when needed.
• Use AI coding agents such as Claude Code and Codex as a core part of the development workflow.
What we're looking for
• Hands-on experience building or improving recommendation systems, search ranking or personalization in production.
• Strong understanding of retrieval, ranking, ML models and experimentation.
• Ability to design and own systems end-to-end, not just individual models.
• Solid software engineering and backend development skills.
• Experience working with user behavior data and measuring product impact.
• Product mindset and ability to make independent technical decisions.
• Comfort working in a small team with evolving priorities.
• Interest in AI-first engineering and using coding agents in daily development.
Experience in e-commerce, marketplaces, consumer products or discovery platforms is a plus.
We care more about what you've built and the impact you've made than a particular tech stack or job title.
What makes this role different
• Real ownership. You'll help define the recommendation architecture and decide what to build, not just implement predefined tasks.
• Experienced founders. Work directly with second-time founders who have already built and exited a company.
• Small team, direct impact. Your decisions will directly influence the product and how users experience it.
• AI-first development. AI coding agents are part of how we build software, not an occasional productivity tool.
• Equity. Share in the long-term success of the company.
• Flexibility. Remote work, with Warsaw preferred and an office available for local teammates.
If you enjoy building intelligent systems, solving ambiguous problems and owning the results of your work, we'd love to hear from you.
The team is building a product that helps people find scents based on their preferences, emotions, and the experiences they're looking for.
Behind the product are second-time founders with a successful exit and experience at Pinterest. It's a small, talented team building something where search, recommendations, and personalization are at the heart of the user experience.
We're looking for a Recommendation Systems Engineer to take ownership of how the product understands user preferences and recommends fragrances.
You'll work directly with the founders, engineers, and product team to design, build, and improve recommendation systems from the ground up.
What you'll work on
• Design and build personalized recommendation systems, semantic search and similar-fragrance discovery.
• Develop candidate retrieval, ranking and re-ranking approaches.
• Solve cold-start challenges and identify useful user signals.
• Build data pipelines and ML-powered services that support recommendations.
• Define evaluation metrics, run experiments and measure recommendation quality.
• Make practical architecture decisions and take systems from idea to production.
• Contribute to backend and product engineering when needed.
• Use AI coding agents such as Claude Code and Codex as a core part of the development workflow.
What we're looking for
• Hands-on experience building or improving recommendation systems, search ranking or personalization in production.
• Strong understanding of retrieval, ranking, ML models and experimentation.
• Ability to design and own systems end-to-end, not just individual models.
• Solid software engineering and backend development skills.
• Experience working with user behavior data and measuring product impact.
• Product mindset and ability to make independent technical decisions.
• Comfort working in a small team with evolving priorities.
• Interest in AI-first engineering and using coding agents in daily development.
Experience in e-commerce, marketplaces, consumer products or discovery platforms is a plus.
We care more about what you've built and the impact you've made than a particular tech stack or job title.
What makes this role different
• Real ownership. You'll help define the recommendation architecture and decide what to build, not just implement predefined tasks.
• Experienced founders. Work directly with second-time founders who have already built and exited a company.
• Small team, direct impact. Your decisions will directly influence the product and how users experience it.
• AI-first development. AI coding agents are part of how we build software, not an occasional productivity tool.
• Equity. Share in the long-term success of the company.
• Flexibility. Remote work, with Warsaw preferred and an office available for local teammates.
If you enjoy building intelligent systems, solving ambiguous problems and owning the results of your work, we'd love to hear from you.