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Machine learning algorithms jobs in 2026 — demand, top roles hiring, and related skills

As of 2026-09-30, Machine learning algorithms appears in 265 job postings indexed by Skillenai over the past 90 days — Data Scientist has the most postings mentioning Machine learning algorithms, with demand share down 14.1% vs the prior 4 weeks.

Last updated · 90d ending 2026-09-30

Postings · last 90 days
265
Demand vs prior month
down 14.1% vs the prior 4 weeks
Top role · 23.0% of skill postings
Data Scientist
Top hiring metro
New York City

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Frequently asked questions about Machine learning algorithms

+Is Machine learning algorithms in demand in 2026?

Yes. Machine learning algorithms appears in 265 job postings indexed by Skillenai over the 90 days ending 2026-09-30. Data Scientist accounts for the most postings mentioning Machine learning algorithms (23.0% of all postings mentioning Machine learning algorithms).

+What jobs require Machine learning algorithms?

According to the Skillenai jobs index over the 90 days ending 2026-09-30, among roles with at least 20 postings, the highest shares mentioning Machine learning algorithms are Lecturer (17.4% of that role’s postings mention Machine learning algorithms), ML Infrastructure Engineer (8.3% of that role’s postings mention Machine learning algorithms), Product Director (6.5% of that role’s postings mention Machine learning algorithms).

+What skills are commonly paired with Machine learning algorithms?

Across job postings indexed by Skillenai (90 days ending 2026-09-30), Machine learning algorithms most often appears alongside Python, SQL, PyTorch, TensorFlow, R.

+Where is Machine learning algorithms most in demand?

As of 2026-09-30, the metro areas posting the most jobs requiring Machine learning algorithms are New York City, Bengaluru, Mountain View, Hyderabad, Paris, according to the Skillenai jobs index.

+How can I keep up with new Machine learning algorithms content and jobs?

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

+Which skills come before and after Machine learning algorithms?

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 Machine learning algorithms — last 90 days

Salary distribution

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

Career paths around Machine learning algorithms

Skills documented before and after this skill across employer changes.

Historical career profiles · all locations

Skills before Machine learning algorithms

Before Machine learning algorithmspython → Machine learning algorithms: 20 observed employer moves with this skill pairsql → Machine learning algorithms: 11 observed employer moves with this skill pairPower BI → Machine learning algorithms: 8 observed employer moves with this skill pairdata analysis → Machine learning algorithms: 8 observed employer moves with this skill pairTableau → Machine learning algorithms: 8 observed employer moves with this skill pairExcel → Machine learning algorithms: 7 observed employer moves with this skill pairJavaScript → Machine learning algorithms: 7 observed employer moves with this skill pairmachine learning models → Machine learning algorithms: 6 observed employer moves with this skill pairMachinelearningalgorithmspython: 20 movespython20 movessql: 11 movessql11 movesPower BI: 8 movesPower BI8 movesdata analysis: 8 movesdata analysis8 movesTableau: 8 movesTableau8 movesExcel: 7 movesExcel7 movesJavaScript: 7 movesJavaScript7 movesmachine learning models: 6 movesmachine learningmodels6 moves

Skills after Machine learning algorithms

After Machine learning algorithmsMachine learning algorithms → sql: 26 observed employer moves with this skill pairMachine learning algorithms → python: 25 observed employer moves with this skill pairMachine learning algorithms → Power BI: 17 observed employer moves with this skill pairMachine learning algorithms → Tableau: 14 observed employer moves with this skill pairMachine learning algorithms → Excel: 12 observed employer moves with this skill pairMachine learning algorithms → machine learning models: 9 observed employer moves with this skill pairMachine learning algorithms → ETL: 8 observed employer moves with this skill pairMachine learning algorithms → sentiment analysis: 6 observed employer moves with this skill pairMachinelearningalgorithmssql: 26 movessql26 movespython: 25 movespython25 movesPower BI: 17 movesPower BI17 movesTableau: 14 movesTableau14 movesExcel: 12 movesExcel12 movesmachine learning models: 9 movesmachine learningmodels9 movesETL: 8 movesETL8 movessentiment analysis: 6 movessentiment analysis6 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: python20
Before: sql11
Before: Power BI8
Before: data analysis8
Before: Tableau8
Before: Excel7
Before: JavaScript7
Before: machine learning models6
After: sql26
After: python25
After: Power BI17
After: Tableau14
After: Excel12
After: machine learning models9
After: ETL8
After: sentiment analysis6

Roles most likely to require Machine learning algorithms

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

RolePostings mentioning skill% of role postings mentioning skill
Lecturer417.4%
ML Infrastructure Engineer48.3%
Product Director36.5%
AI Data Scientist15.0%
Data Science Consultant34.1%
Data Security Engineer13.8%
AI Scientist33.4%
Machine Learning Research Engineer12.9%
Business Intelligence Specialist12.6%
Principal Data Scientist12.5%

Roles with the most Machine learning algorithms postings

RolePostings mentioning skillShare of skill postings
Data Scientist6123.0%
Machine Learning Engineer3613.6%
Software Engineer166.0%
ML Engineer103.8%
Data Analyst93.4%
AI/ML Engineer51.9%
AI Engineer41.5%
Business Analyst41.5%
Lecturer41.5%
ML Infrastructure Engineer41.5%

Top companies posting jobs requiring Machine learning algorithms

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

Top companies posting jobs requiring Machine learning algorithms
CompanyPostings · 90 days
Novartis9
Waymo8
Nimble Storage6
Sggovterp4
Eightfold4
General Motors4
Mastercard3
Mistral3
Captivation3
NiCE3

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 Machine learning algorithms

NamePostingsShare
New York City134.9%
Bengaluru83.0%
Mountain View83.0%
Hyderabad72.6%
Paris62.3%
Pune62.3%
Singapore62.3%
Toronto62.3%
San Jose51.9%

Skills commonly paired with Machine learning algorithms

Python (204)SQL (93)PyTorch (66)TensorFlow (63)R (63)data visualization (60)AWS (42)scikit-learn (38)deep learning (35)Statistical modeling (34)

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How this was computed

Counts derive from the Skillenai jobs index over the 90 days ending 2026-09-30. 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 Machine learning algorithms by all postings for each role in the same window, ranking roles with at least 20 postings. Role distribution divides each role’s Machine learning algorithms postings by all Machine learning algorithms 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). Adjusted posting share: 0.1% to 0.1%. Demand share change is the relative percentage change between these adjusted shares. Each employer-and-ATS group has at least 10 postings in each 90-day window; its earlier posting count supplies the same weight in both windows. The panel includes 2,595 identified employers and covers 68% of earlier and 72% of latest indexed postings. Windows: 2026-06-02 to 2026-08-31 and 2026-06-30 to 2026-09-28 (UTC; end dates excluded). The windows overlap by 62 days. Dates reflect indexing, not the employer’s posting date. This measures posting mix, not total hiring or market-wide demand. Matching excludes entrants and exits; changes in crawl completeness within an employer or ATS can still affect the result.

source
Skillenai jobs index, deduplicated daily
entity_id
17ca308273065612
data_as_of
2026-09-30
window_days
90
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The demand, skills, and geo numbers on this page come from the same Skillenai labor market index that powers our API. Use it for compensation benchmarking, hiring-competition analysis, and skill-adoption tracking.

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Compiled by Jared Rand · Data sourced from the Skillenai labor market index