AI Job Matching & Role-Scoring Methodology
How Fastlyy evaluates newly indexed engineering, AI, and product openings against your skills using deep semantic embeddings to compute a clear, transparent 0 to 100% Match Score.
Senior Distributed Systems Engineer
Stripe • Remote (US) • Greenhouse ATS
Go, Kafka, Distributed Consensus, High-Throughput APIs
5+ Years distributed backend systems experience
Fintech payment infrastructure and financial ledgers
100% Remote (US/Canada compatible timezones)
The 5 Algorithmic Scoring Factors
Unlike commercial platforms that treat your profile as a bag of keywords, Fastlyy evaluates multi-dimensional suitability across five core components.
Tech Stack & Tooling Semantic Overlap
We extract programming languages, frameworks, cloud tooling, database engines, and architecture paradigms from the job posting. Fastlyy understands synonyms and ecosystem clusters: if you know Next.js, it knows you understand React and SSR; if you know PyTorch, it evaluates your deep learning alignment.
Seniority & Architectural Scope
Evaluating individual contributor vs tech lead vs staff engineer expectations. The model scans for indicators like cross-functional leadership, multi-team roadmap ownership, mentor responsibilities, and system design complexity.
Domain & Industry Alignment
Whether you have experience in high-velocity startup environments, enterprise regulatory environments (fintech, healthcare), frontier AI labs, or high-throughput consumer marketplaces.
Work Arrangement & Location Fit
Matching your stated workplace preferences (Remote, Hybrid, In-Office) against the employer’s official ATS requirements, including geographic restrictions (e.g. US only, EMEA only, Worldwide).
Dream Companies (+15 Points) & Recency Velocity (+10% Weight)
Select your target dream employers in your dashboard. When any monitored company posts a requisition, it receives an automatic +15 point boost to guarantee it pins to the top of your feed.
Why Keyword Search Fails in Modern Tech Hiring
Traditional Keyword Counting (LinkedIn / Indeed)
- •Requires exact substring matches (misses "Golang" if looking for "Go").
- •Cannot tell the difference between building a database vs querying a database.
- •Rewards keyword stuffing and buzzword density over verified project achievements.
Fastlyy DeepSeek Semantic Matching
- Maps technologies conceptually into vector embeddings for nuanced equivalence.
- Extracts action verbs and measurable metric outcomes (latency, throughput, revenue).
- Ranks genuine architectural ownership higher than passive technology mentions.
Frequently Asked Questions
Can I adjust or override my AI match preferences?
Yes. In your Fastlyy settings, you can tune your target seniority level, preferred tech stack, minimum salary expectations, and geographic boundaries. You can also re-upload an updated resume at any time to refresh your candidate embedding.
How does the Resume Roast feature integrate with role matching?
Our Roast My Resume tool evaluates your resume against modern ATS criteria (metric density, bullet length, passive voice). Optimizing your resume with those suggestions directly improves your semantic match score across open requisitions.
See your personalized match score across live roles
Upload your resume or set your target skills to see exact 0-100% match scores on open tech roles across 1,000+ company career portals.