Skillenai

data labeling jobs in 2026 — demand, top roles hiring, and related skills

As of 2026-11-05, data labeling appears in 705 job postings indexed by Skillenai over the past 90 days — Machine Learning Engineer has the most postings mentioning data labeling.

Last updated · 90d ending 2026-11-05

Postings · last 90 days
705
Top role · 4.1% of skill postings
Machine Learning Engineer
Top hiring metro
San Francisco

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Frequently asked questions about data labeling

+Is data labeling in demand in 2026?

Yes. data labeling appears in 705 job postings indexed by Skillenai over the 90 days ending 2026-11-05. Machine Learning Engineer accounts for the most postings mentioning data labeling (4.1% of all postings mentioning data labeling).

+What jobs require data labeling?

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 data labeling are Quality Control Specialist (42.9% of that role’s postings mention data labeling), AI Tutor (34.5% of that role’s postings mention data labeling), AI Data Annotator (34.1% of that role’s postings mention data labeling).

+What skills are commonly paired with data labeling?

Across job postings indexed by Skillenai (90 days ending 2026-11-05), data labeling most often appears alongside Python, data annotation, machine learning, annotation, model evaluation.

+Where is data labeling most in demand?

As of 2026-11-05, the metro areas posting the most jobs requiring data labeling are San Francisco, Sunnyvale, Boston, New York City, Palo Alto, according to the Skillenai jobs index.

+How can I keep up with new data labeling content and jobs?

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

+Which skills come before and after data labeling?

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 data labeling — last 90 days

Salary distribution

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

Career paths around data labeling

Skills documented before and after this skill across employer changes.

Historical career profiles · all locations

Skills before data labeling

Before data labelingTableau → data labeling: 2 observed employer moves with this skill pairspark → data labeling: 1 observed employer moves with this skill pairAWS (EMR, S3, Redshift) → data labeling: 1 observed employer moves with this skill pairETL → data labeling: 1 observed employer moves with this skill pairAUC → data labeling: 1 observed employer moves with this skill pairBloom Filters → data labeling: 1 observed employer moves with this skill pairMYSQL → data labeling: 1 observed employer moves with this skill pairsegmentation → data labeling: 1 observed employer moves with this skill pairdata labelingTableau: 2 movesTableau2 movesspark: 1 movesspark1 movesAWS (EMR, S3, Redshift): 1 movesAWS (EMR, S3,Redshift)1 movesETL: 1 movesETL1 movesAUC: 1 movesAUC1 movesBloom Filters: 1 movesBloom Filters1 movesMYSQL: 1 movesMYSQL1 movessegmentation: 1 movessegmentation1 moves

Skills after data labeling

After data labelingdata labeling → usability testing: 1 observed employer moves with this skill pairdata labeling → Environment Layer: 1 observed employer moves with this skill pairdata labeling → a/b testing: 1 observed employer moves with this skill pairdata labeling → python: 1 observed employer moves with this skill pairdata labeling → clustering algorithms: 1 observed employer moves with this skill pairdata labeling → Azure Databricks: 1 observed employer moves with this skill pairdata labeling → data retrieval: 1 observed employer moves with this skill pairdata labeling → dataset pipeline: 1 observed employer moves with this skill pairdata labelingusability testing: 1 movesusability testing1 movesEnvironment Layer: 1 movesEnvironment Layer1 movesa/b testing: 1 movesa/b testing1 movespython: 1 movespython1 movesclustering algorithms: 1 movesclusteringalgorithms1 movesAzure Databricks: 1 movesAzure Databricks1 movesdata retrieval: 1 movesdata retrieval1 movesdataset pipeline: 1 movesdataset pipeline1 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: Tableau2
Before: spark1
Before: AWS (EMR, S3, Redshift)1
Before: ETL1
Before: AUC1
Before: Bloom Filters1
Before: MYSQL1
Before: segmentation1
After: usability testing1
After: Environment Layer1
After: a/b testing1
After: python1
After: clustering algorithms1
After: Azure Databricks1
After: data retrieval1
After: dataset pipeline1

Roles most likely to require data labeling

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

RolePostings mentioning skill% of role postings mentioning skill
Quality Control Specialist1242.9%
AI Tutor1934.5%
AI Data Annotator1534.1%
AI Safety Evaluator826.7%
AI Training Expert1626.2%
AI Training Specialist922.0%
AI Response Evaluator520.0%
AI Evaluator918.0%
Algorithm Engineer716.7%
AI Evaluation Expert915.5%

Roles with the most data labeling postings

RolePostings mentioning skillShare of skill postings
Machine Learning Engineer294.1%
Software Engineer202.8%
AI Tutor192.7%
AI Trainer182.6%
Data Scientist172.4%
AI Training Expert162.3%
Product Manager162.3%
AI Data Annotator152.1%
AI Quality Evaluator131.8%
Data Analyst131.8%

Top companies posting jobs requiring data labeling

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

Top companies posting jobs requiring data labeling
CompanyPostings · 90 days
OpenBrain248
Welo Data49
xAI20
Canva15
Remote13
TSMG12
Weloglobal11
Beacon Biosignals10
CLERA9
Amazon7

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 data labeling

NamePostingsShare
San Francisco486.8%
Sunnyvale111.6%
Boston91.3%
New York City91.3%
Palo Alto91.3%
Berlin81.1%
Mountain View71.0%
London60.9%
Amsterdam40.6%

Skills commonly paired with data labeling

Python (131)data annotation (113)machine learning (96)annotation (92)model evaluation (89)quality assurance (85)AI training (74)SQL (62)PyTorch (59)data pipelines (50)

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 data labeling by all postings for each role in the same window, ranking roles with at least 20 postings. Role distribution divides each role’s data labeling postings by all data labeling 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
6210150622556b0b
data_as_of
2026-11-05
window_days
90
Compiled by Jared Rand · Data sourced from the Skillenai labor market index