APPLYDJINN

Machine Learning jobs and hiring demand in WA, United States

Core and required roles are separated from contextual and optional mentions so the headline does not overstate job intent.

Explore Machine Learning by location
WA, United States

Select up to five markets; results and hiring evidence update together.

101core + required roles248context + optional mentions5remote-friendly▼ -66 this week

Employer concentration

Amazon accounts for 171 of 349 mentions (49%). The remaining 178 mentions span other employers.

View without top 1 employer →View without top 3 employers →
Machine Learning market intelligence visualization

Model work connected to product and operational evidence

Machine Learning market guide

Machine-learning demand covers model development, applied engineering, data pipelines, evaluation, platform work, and domain-specific products. The job title alone rarely reveals which part of the lifecycle matters most.

349 live roles22 hiring companies1% remote-friendly

Vacancy evidence map

Where Machine Learning carries hiring weight

Each segment represents roles where Machine Learning was parsed at that evidence tier. This keeps a required production skill separate from contextual stack language.

39 Core62 Required194 Supporting54 Optional
101core + required29% of mentions
15.9roles per company22 employers

Market interpretation

What Machine Learning demand means in practice

ApplyDjinn’s evidence tiers help distinguish roles where ML is the product or primary craft from roles where it is supporting context. Companion technologies show whether employers emphasize experimentation, data engineering, deployment, inference, computer vision, NLP, or generative AI.

Strong applications explain the data, baseline, metric, validation approach, deployment boundary, and monitoring plan. Model choice matters, but evidence of reliable evaluation and product impact usually travels farther than an isolated accuracy claim.

Applied MLML platform / MLOpsData scienceAI product engineering

Reading the market

Signals to look for

  • Python, SQL, cloud, data pipelines, and model frameworks form the recurring foundation.
  • MLOps and platform roles emphasize reproducibility, deployment, observability, and cost.
  • Applied roles often value domain data and product judgment alongside modelling depth.

Geographic demand

Top Machine Learning locations

United States348Washington, United States268Seattle, Washington, United States184California, United States66Bellevue, Washington, United States65WA, United States59San Francisco, California, United States47CA, United States36

Questions candidates ask

Machine Learning hiring FAQ

What is the difference between AI and machine-learning vacancies?

AI is a broader market label that can include workflow and product roles; ML vacancies more often require model, data, evaluation, or deployment depth.

What portfolio evidence is useful for ML roles?

A reproducible project with a baseline, honest validation, error analysis, deployment considerations, and a clear account of personal contribution.

How Machine Learning appears in job requirements

Inferred from the title and requirement wording in 349 active roles; each role is counted once. Read the methodology.

Posting evidence, not a company-wide stack claim
Main / core
11%(39)
Required
18%(62)
Supporting / context
56%(194)
Nice-to-have
15%(54)

Skills mentioned with Machine Learning

A shared posting does not always require both skills. Explicit alternatives are counted separately.

AI281 together30 both required2 alternativesScalability162 together9 both required1 alternativesCloud148 together14 both required1 alternativesPython118 together28 both required1 alternativesAWS113 together12 both requiredAutomation80 together5 both required

Role graph

Roles hiring for Machine Learning

Software Engineering 104Machine Learning & AI 54Product Management 26Data Science 12Sales & Account Management 12Application Security 11Finance & Accounting 9Project & Program Management 9

Latest roles mentioning Machine Learning

Applied AI Engineer, Public Sector

Nice

Anthropic — Washington, District of Columbia, United States

Senior Developer Relations Manager - Dynamo AI Inference

Required

NVIDIA — CA, Santa Clara, United States; NY, New York, United States; WA, Seattle, United States

Analyst, Content Safety

Nice

Google — Kirkland, WA, United States

Operations Engineer II, AWS Managed Services (AMS)

Context

Amazon — Seattle, Washington, United States

Business Intelligence Engineer, Forecasting & Labs Analytics

Required

Amazon — Bellevue, Washington, United States

Senior Applied Scientist, AWS Healthcare AI

Context

Amazon — Seattle, Washington, United States

View all 349 roles mentioning Machine Learning →