Question 1

Which companies hire Recommendation Systems specialists on a 4-day work week?

Accepted Answer

Employers hiring for Recommendation Systems on this page include Spotify, Airbnb, and Postman. Recommendation Systems roles appear most frequently in engineering, data, and platform teams at companies that have adopted a reduced-hours schedule. Each listing indicates the seniority level and whether Recommendation Systems is a primary requirement or one of several preferred skills — expand any role above to see the full stack and responsibilities.

Question 2

What seniority levels commonly hire for Recommendation Systems on reduced-hours schedules?

Accepted Answer

Recommendation Systems roles span the full seniority range — we list 10 open roles requiring Recommendation Systems across entry-level, mid-level, senior, lead, and staff/principal positions. Senior and above tend to dominate because employers offering reduced-hours schedules often lean toward experienced individual contributors who can deliver consistently in fewer hours. Filter by level in the sidebar to narrow the list above.

Question 3

How should I position Recommendation Systems experience for 4-day-week applications?

Accepted Answer

Lead with measurable outcomes over time spent — Recommendation Systems hiring managers at reduced-hours companies care about delivered value, not hours worked. Highlight projects where you shipped at a steady cadence, collaborated asynchronously, or reduced engineering toil through automation or tooling. Include concrete metrics (latency improvements, adoption numbers, cost reductions) rather than vague duty descriptions. Expand listings above to see the exact framing each employer uses in their job descriptions.

Question 4

Do Recommendation Systems salaries at 4-day-week companies match 5-day employers?

Accepted Answer

Yes — companies listed on 4dayweek.io commit to full salary parity regardless of schedule. Recommendation Systems roles in tech and data typically command premium rates at both reduced-hours and traditional employers. Specific ranges depend on seniority, location, and the specific sub-specialty (e.g. backend vs frontend, infra vs ML). Individual listings above show exact bands where the employer publishes them.

Question 5

Which complementary skills strengthen a Recommendation Systems application?

Accepted Answer

Depends on the role, but Recommendation Systems candidates who also demonstrate async communication, clean documentation, and cross-functional collaboration are typically strong fits for reduced-hours employers — those companies rely on written-first communication and high-context handoffs to operate on a compressed schedule. Technical-adjacent skills vary by stack. Browse the top skills shown in the sidebar to see which tags co-occur most often with Recommendation Systems on current listings.

Recommendation Systems Jobs

10 Jobs Found

Staff Machine Learning Engineer, Home Podcast

Senior Machine Learning Engineer, Personalization

Senior Staff ML Engineer, Search & Recommendation

Machine Learning Engineer

Senior Staff Machine Learning Engineer

Machine Learning Engineer

Staff Machine Learning Engineer, Listings and Host Tools Data and AI

Senior Machine Learning Engineer - Personalization

Senior Engineer, Search

Research Scientist - Personalization

Top Companies Hiring

Frequently Asked Questions

10 Jobs Found

Staff Machine Learning Engineer, Home Podcast

Senior Machine Learning Engineer, Personalization

Senior Staff ML Engineer, Search & Recommendation

Machine Learning Engineer

Senior Staff Machine Learning Engineer

Machine Learning Engineer

Staff Machine Learning Engineer, Listings and Host Tools Data and AI

Senior Machine Learning Engineer - Personalization

Senior Engineer, Search

Research Scientist - Personalization

Top Companies Hiring

Frequently Asked Questions

Jobs by Location

Popular Skills