information retrieval jobs in 2026 — demand, top roles hiring, and related skills

As of 2026-11-05, information retrieval appears in 723 job postings indexed by Skillenai over the past 90 days — Software Engineer has the most postings mentioning information retrieval.

Last updated · 90d ending 2026-11-05

Postings · last 90 days
723
Top role · 43.4% of skill postings
Top hiring metro
Warsaw

Which roles want information retrieval?

Upload your resume and Skillenai will show which roles your information retrieval experience fits, which skills you already cover, and what is missing.

Frequently asked questions about information retrieval

+Is information retrieval in demand in 2026?

Yes. information retrieval appears in 723 job postings indexed by Skillenai over the 90 days ending 2026-11-05. Software Engineer accounts for the most postings mentioning information retrieval (43.4% of all postings mentioning information retrieval).

+What jobs require information retrieval?

According to the Skillenai jobs index over the 90 days ending 2026-11-05, among roles with at least 20 postings, the highest shares mentioning information retrieval are Search Engineer (20.0% of that role’s postings mention information retrieval), Applied Research Scientist (7.4% of that role’s postings mention information retrieval), Software Engineering Manager (6.2% of that role’s postings mention information retrieval).

+What skills are commonly paired with information retrieval?

Across job postings indexed by Skillenai (90 days ending 2026-11-05), information retrieval most often appears alongside Natural language processing, networking, Distributed computing, large-scale system design, Python.

+Where is information retrieval most in demand?

As of 2026-11-05, the metro areas posting the most jobs requiring information retrieval are Warsaw, Mountain View, New York City, London, San Francisco, according to the Skillenai jobs index.

+How can I keep up with new information retrieval content and jobs?

Skillenai indexes news, blog posts, and research papers mentioning information retrieval alongside the jobs index. You can subscribe to a daily email digest of new information retrieval content from your Skillenai account.

+Which skills come before and after information retrieval?

The skill-flow chart shows skills documented in adjacent positions across observed employer changes. An outgoing skill is documented in the following position but not the preceding one. These are ideas to explore, not proven prerequisites, acquisition dates, or levels of mastery. Each ribbon counts employer moves with that skill pair; one move can contribute several pairs.

Weekly indexed postings requiring information retrieval — last 90 days

Salary distribution

Box = 25th–75th percentile · tick = median · whisker = 10th–90th · USD, annualized

Career paths around information retrieval

Skills documented before and after this skill across employer changes.

Historical career profiles · all locations

Skills before information retrieval

Before information retrievalchurning customers → information retrieval: 1 observed employer moves with this skill pairETL → information retrieval: 1 observed employer moves with this skill pairvisualizations → information retrieval: 1 observed employer moves with this skill paircosine similarity → information retrieval: 1 observed employer moves with this skill pairpython → information retrieval: 1 observed employer moves with this skill pairmachine learning algorithms → information retrieval: 1 observed employer moves with this skill paircompilers → information retrieval: 1 observed employer moves with this skill pairdatabase software → information retrieval: 1 observed employer moves with this skill pairinformationretrievalchurning customers: 1 moveschurning customers1 movesETL: 1 movesETL1 movesvisualizations: 1 movesvisualizations1 movescosine similarity: 1 movescosine similarity1 movespython: 1 movespython1 movesmachine learning algorithms: 1 movesmachine learningalgorithms1 movescompilers: 1 movescompilers1 movesdatabase software: 1 movesdatabase software1 moves

Skills after information retrieval

After information retrievalinformation retrieval → spark: 1 observed employer moves with this skill pairinformation retrieval → stateful multi-process execution: 1 observed employer moves with this skill pairinformation retrieval → supervised learning: 1 observed employer moves with this skill pairinformation retrieval → autonomous-driving: 1 observed employer moves with this skill pairinformation retrieval → user experience: 1 observed employer moves with this skill pairinformation retrieval → sql: 1 observed employer moves with this skill pairinformation retrieval → Powerpoint: 1 observed employer moves with this skill pairinformation retrieval → model evaluation: 1 observed employer moves with this skill pairinformationretrievalspark: 1 movesspark1 movesstateful multi-process execution: 1 movesstatefulmulti-processexecution1 movessupervised learning: 1 movessupervisedlearning1 movesautonomous-driving: 1 movesautonomous-driving1 movesuser experience: 1 movesuser experience1 movessql: 1 movessql1 movesPowerpoint: 1 movesPowerpoint1 movesmodel evaluation: 1 movesmodel evaluation1 moves
How to read this chart · view counts

Each side is an independent set of observed employer moves, not the same people followed through three stages. Ribbon widths compare move counts within that side. Internal moves are not included.

The following position documents a skill that the preceding position does not. Skills must be linked to both positions, with clear dates and no overlap. One move can connect several skill pairs. These patterns suggest skills to explore; they do not establish prerequisites, when a skill was learned, or a higher skill level.

Source: Skillenai talent graph, historical career profiles. Historical descriptions and coverage can change. Only the leading published connections are shown.

Observed connections and move counts
ConnectionMoves
Before: churning customers1
Before: ETL1
Before: visualizations1
Before: cosine similarity1
Before: python1
Before: machine learning algorithms1
Before: compilers1
Before: database software1
After: spark1
After: stateful multi-process execution1
After: supervised learning1
After: autonomous-driving1
After: user experience1
After: sql1
After: Powerpoint1
After: model evaluation1

Roles most likely to require information retrieval

Among roles with at least 20 postings in the same period.

RolePostings mentioning skill% of role postings mentioning skill
Search Engineer520.0%
Applied Research Scientist27.4%
Software Engineering Manager496.2%
Applied Scientist145.8%
Principal Data Scientist25.3%
Machine Learning Engineering Manager34.9%
Research Software Engineer14.5%
Machine Learning Manager14.2%
Back End Developer14.0%
Lead Developer13.8%

Roles with the most information retrieval postings

RolePostings mentioning skillShare of skill postings
Software Engineer31443.4%
Machine Learning Engineer709.7%
Software Engineering Manager496.8%
Data Scientist456.2%
AI Engineer263.6%
ML Engineer233.2%
Product Manager233.2%
Applied Scientist141.9%
Engineering Manager141.9%
Research Scientist71.0%

Top companies posting jobs requiring information retrieval

Employers ranked by indexed job postings in the last 90 days.

Top companies posting jobs requiring information retrieval
CompanyPostings · 90 days
Google321
Elsevier32
LinkedIn11
Pinterest11
Etsy10
Reuters10
YouTube9
Elastic9
ServiceNow9
Workday8

Job postings indexed over the past 90 days, grouped by resolved employer. Counts are postings, not hires. Companies without a published page appear without a link.

Top metros hiring for information retrieval

NamePostingsShare
Warsaw324.4%
Mountain View273.7%
New York City182.5%
London172.4%
San Francisco172.4%
Seattle172.4%
Dublin131.8%
Paris101.4%
Bengaluru91.2%

Skills commonly paired with information retrieval

Explore related pages

How this was computed

Weekly job-count charts omit the incomplete current week (weeks start Monday, UTC). Totals include all postings in the stated window. Counts derive from the Skillenai jobs index over the 90 days ending 2026-11-05. Skills are resolved against the Skillenai canonical taxonomy, so the same entity is counted whether a posting writes 'Python', 'Python 3', or 'python'. Role prevalence divides postings mentioning information retrieval by all postings for each role in the same window, ranking roles with at least 20 postings. Role distribution divides each role’s information retrieval postings by all information retrieval postings, including postings without a role. Shares need not sum to 100% for the displayed roles. Pages refresh weekly (or daily for the top-50 most-requested skills). An adjusted trend is not shown because comparable posting coverage is insufficient.

source
Skillenai jobs index, deduplicated daily
entity_id
a37c1b1fb70b5e8f
data_as_of
2026-11-05
window_days
90
Compiled by Jared Rand · Data sourced from the Skillenai labor market index