Seattle, WA

Salary
$167,100–$226,100from the description
Posted
Jul 16, 2026
Location
Seattle, WA
Last confirmed open
Jul 21, 2026

What this job asks for AI summary

A senior machine learning scientist role focused on building predictive models for marketing use cases — primarily lead scoring, customer segmentation, and account prioritization. Day-to-day work spans designing and deploying deep learning pipelines (including transformer and graph-based architectures), running causal experiments, and collaborating with MLOps teams to move models into production. Suits researchers with strong applied ML experience who are comfortable bridging novel methods and real business outcomes.

Senior level · 6+ years · Austin, TX · Master's required · Full-time

Must have (11)
PythonPyTorch or TensorFlowdeep learningmachine learningSQLSparkJava or C++recommender systemstransformersstatistical analysisexperimental design
Nice to have (7)
AWS SageMaker or MLflowBERTLLMsCI/CDfederated learningGANsdiffusion models

“or” means any one of them counts — you don't need all of them.

We read this from the posting text with AI. Skim the description below before ruling yourself out.

How this req sits in the market our data

Roughly 6 people in the Austin, TX area plausibly meet what this posting asks for (data scientists). range 3–8

Applicant volume Light — Few people clear these requirements, so an application that does clear them gets looked at. Worth applying to even if you miss a nice-to-have.

What gives you an edge
recommender systems3%experimental design4%transformers9%

Rare in this occupation — lead with these, and say what you built with them.

What won't set you apart
Python88%machine learning80%SQL72%statistical analysis60%deep learning40%

Most people in this occupation already list these. Still required — just not what gets you shortlisted.

What the occupation pays Median $130,161 (middle half $87,666–$165,113). This posting is about at that midpoint.

Estimated from BLS employment for this occupation and area, per-skill prevalence across our listing corpus, and published wage benchmarks — as of Jul 28, 2026. It is a model, not a headcount.

Why we read it this way (6)

The degree requirement is a structured OR: PhD alone, OR Master's + 6 years of applied research experience. A Bachelor's is not listed as an accepted path, so Master's is set as the minimum formal degree gate.

The role also states '3+ years of building ML models for business application' as a separate basic qualification; the 6-year figure (tied to the Master's path) is used as the overall years minimum since it represents the higher, more constraining experience gate.

Java and C++ appear in the Basic Qualifications alongside Python ('Java, C++, Python or related language'); Java is listed as the primary skill with C++ as an alternative, and Python is captured separately as its own hard gate given the explicit 'Proficiency in Python' requirement.

AWS SageMaker and MLflow appear in the responsibilities narrative ('tools like AWS SageMaker, or MLflow') rather than under a formal requirements heading, so they are marked preferred.

BERT, GANs, diffusion models, LLMs (fine-tuning), CI/CD, and federated learning all appear under the 'Preferred Qualifications' section.

The compensation range ($167,100–$226,100/year) is for Austin, TX; Amazon notes final pay depends on experience, qualifications, and location. Sign-on payments and RSUs are also part of the package.

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