ML Engineer Salary in Seattle 2026: $155K–$320K Complete Guide

Seattle has emerged as one of the world’s premier markets for machine learning engineers. While San Francisco and New York compete for the top of the ML salary rankings, Seattle’s combination of Amazon’s massive AI investment, Microsoft’s OpenAI partnership and Research division, Meta’s FAIR lab, Google’s DeepMind presence, and the Allen Institute for AI creates a concentration of ML opportunity that is genuinely unmatched outside the Bay Area — with a critical financial advantage: zero state income tax.

This guide covers exactly what ML engineers earn in Seattle in 2026, broken down by experience level, by employer, and after taxes — plus the skills that move you into the top quartile of the market.

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Seattle ML Engineering Market Overview

Seattle’s ML ecosystem is anchored by five major forces:

Amazon AI is the defining employer of ML talent in Seattle. Across Amazon Science, Alexa AI, Amazon Advertising, AWS AI/ML, Amazon Robotics, and Prime Video’s recommendation systems, Amazon employs thousands of ML engineers working on some of the highest-scale systems in the world. Amazon’s L5–L7 ML engineering ladder is one of the most well-defined in the industry, with transparent progression and predictable compensation growth. Microsoft Research and Azure AI represent the second pillar. Microsoft’s $13B+ investment in OpenAI has turbocharged ML hiring across its Redmond and Seattle campuses. The Azure AI platform, Copilot infrastructure, Bing AI, and Microsoft Research (which has published foundational ML papers for three decades) collectively make Microsoft one of the most important ML employers in the Pacific Northwest. Meta FAIR Seattle is smaller but highly selective. Meta’s Fundamental AI Research lab has a significant Seattle presence focused on foundational model research. FAIR researchers and engineers are among the best-compensated ML professionals in the city, with comp packages that routinely include outsized RSU grants. Google DeepMind and Google Brain maintain a meaningful Seattle footprint. Google’s Seattle office works across Search AI, YouTube recommendations, and increasingly on DeepMind-related applied research. Google’s ML compensation competes head-to-head with Amazon and Microsoft at the senior level. Allen Institute for AI (AI2) is Seattle’s crown jewel of ML research. Founded by Paul Allen and led by world-class researchers, AI2 produces foundational work on language models, computer vision, and scientific AI. While compensation is below FAANG, AI2 attracts ML engineers and researchers who prioritize impact and publication record over maximum pay.

Beyond these anchors, Seattle has a growing ML startup ecosystem — including AI-native companies building on top of foundation models, specialized ML infrastructure startups, and enterprise AI companies. These roles typically offer lower base salaries but meaningful equity upside.

ML Engineer Salary in Seattle by Experience Level

Junior ML Engineer (0–2 years)

Base salary: $120,000–$155,000 Total compensation: $140,000–$185,000 Typical employers: Amazon (L4), Microsoft (SDE II), startups, AI2 research assistant roles

Junior ML engineers in Seattle typically have strong Python skills, familiarity with PyTorch or TensorFlow, and foundational knowledge of ML algorithms from academic or bootcamp backgrounds. At Amazon, L4 new-grad ML engineers earn $150K–$185K total comp with RSUs; Microsoft SDE IIs in ML teams earn $140K–$175K.

Mid-Level ML Engineer (2–5 years)

Base salary: $165,000–$210,000 Total compensation: $195,000–$265,000 Typical employers: Amazon (L5), Microsoft (Senior SDE), Meta (E5), Google (L5)

Mid-level is where the Seattle advantage becomes most visible. An Amazon L5 ML engineer earns $185K–$250K total comp; a Google L5 earns $200K–$270K. At this level, specialization matters significantly: engineers with LLM fine-tuning, MLOps, or production deployment experience command the upper end of these ranges.

Senior ML Engineer (5–10 years)

Base salary: $200,000–$260,000 Total compensation: $255,000–$340,000 Typical employers: Amazon (L6), Microsoft (Principal/Senior SDE), Meta (E6), Google (L6)

Senior ML engineers in Seattle are among the highest-paid engineers in the world, and the Seattle tax advantage amplifies this further. An Amazon L6 ML engineer earns $240K–$320K total comp. At Meta (E6), senior ML researchers earn $270K–$360K. The gap between mid-level and senior is the most financially significant transition in an ML career.

Staff / Principal ML Engineer (10+ years)

Base salary: $250,000–$330,000+ Total compensation: $320,000–$500,000+ Typical employers: Amazon (L7+), Microsoft (Partner/Distinguished), Meta (E7+), Google (L7+)

Staff and principal ML engineers are rare and extremely well-compensated. At Amazon, L7 principal engineers frequently see total comp exceed $400K when RSUs are included. These roles involve setting technical direction for entire product lines, publishing research, and driving cross-organizational ML strategy. Competition for these roles is intense — they are typically filled by internal promotion or targeted recruiting from academic or FAANG pipelines.

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Top ML Employers in Seattle: What They Pay

Amazon AI & Amazon Science

Amazon’s ML compensation is structured around its internal ladder (L4–L8). RSUs vest over 4 years with front-loading in years 3 and 4. The most lucrative ML roles at Amazon are in Amazon Advertising ML (revenue-critical systems), AWS AI/ML (platform and tooling), and Amazon Science (research-to-production pipeline).

Typical Amazon ML engineer total comp by level:

L4: $150K–$185K

L5: $185K–$250K

L6: $240K–$320K

L7: $320K–$480K

Microsoft AI Research and Azure AI

Microsoft’s compensation structure is more predictable than Amazon’s. Base salaries are competitive, and the OpenAI partnership has created new equity pathways via Microsoft’s OpenAI investment. Microsoft’s ML teams working on Copilot, Azure AI, and Bing AI are the highest-compensated.

Typical Microsoft ML engineer total comp:

SDE II (ML): $140K–$175K

Senior SDE (ML): $190K–$250K

Principal SDE (ML): $270K–$370K

Partner/Distinguished: $350K–$550K+

Meta FAIR Seattle

Meta pays among the highest total compensation in Seattle for ML roles. FAIR engineers are compensated at the top of Meta’s E-level ladder, with significant RSU grants.

E5 (Senior): $260K–$340K

E6 (Staff): $320K–$450K

E7 (Principal): $450K–$650K+

Google DeepMind / Google Brain Seattle

Google’s ML compensation is comparable to Amazon at most levels, with a stronger emphasis on signing bonuses and slightly higher base salaries relative to equity.

L5: $200K–$270K

L6: $255K–$340K

L7: $340K–$500K+

Allen Institute for AI (AI2)

AI2 pays below FAANG but offers extraordinary research value:

Research Engineer (mid): $130K–$170K

Senior Research Engineer: $160K–$210K

Research Scientist: $150K–$200K

For engineers pursuing PhDs, academic careers, or research impact, AI2’s compensation disadvantage is often offset by publication opportunities and mission alignment.

ML-Focused Startups

Seattle’s ML startup scene typically pays:

Base salary: 20–30% below FAANG

Equity: 0.05%–0.5% depending on stage and role

Total comp at Series B+ startups can approach or exceed mid-level FAANG if equity appreciates

Compare Seattle ML salaries with software engineer salaries →

The Washington State Tax Advantage

Washington has no state income tax — one of only nine states with this advantage. For ML engineers, this creates a substantial take-home pay difference compared to California (13.3% top marginal rate) or New York (10.9%).

Example: Senior ML Engineer, $230,000 base

Seattle take-home (after federal taxes ~$72K): $158,000

San Francisco take-home (after federal + CA state ~$103K): $127,000

Annual advantage: $31,000+

Over a 5-year senior career, the tax advantage compounds to $150,000–$200,000 in additional take-home pay — before accounting for Seattle’s meaningfully lower housing costs.

Key ML Skills That Command Seattle Premiums

The Seattle ML market rewards specialization heavily. Generic ML generalists earn at the lower end of market ranges; specialists in high-demand areas earn at the top:

LLM Fine-Tuning and Alignment (+$25K–$45K premium) Engineers who can fine-tune large language models, implement RLHF pipelines, and work on model alignment are among the most sought-after professionals in Seattle. Amazon Alexa AI and Microsoft Copilot teams pay exceptional premiums for this expertise. MLOps and Production ML Infrastructure (+$20K–$35K premium) PyTorch, Kubernetes, Kubeflow, MLflow, and Airflow expertise bridges the gap between research and production. Engineers who can take models from notebook to production at scale command significant premiums at every employer. PyTorch and JAX Deep Learning (baseline expectation at senior+) PyTorch is the dominant framework at Meta FAIR, AI2, and most research-oriented teams. TensorFlow/Keras remains relevant at Google. JAX expertise is increasingly valued at frontier AI organizations. Distributed Training and Large-Scale Compute (+$15K–$30K premium) Experience with multi-GPU and multi-node training, model parallelism, and efficient distributed computing is a tier-one differentiator at Amazon, Microsoft, and Meta. Computer Vision and Multimodal AI (+$15K–$25K premium) Seattle has significant demand for computer vision engineers, particularly in Amazon’s robotics, Go (cashierless retail), and delivery optimization systems.

Seattle vs Other ML Hubs

Seattle vs San Francisco Bay Area SF pays 10–20% higher base salaries for ML roles, but Washington’s 0% income tax and 15–20% lower housing costs flip the equation for most engineers. A $200K Seattle ML role often delivers more take-home than a $225K SF role. Seattle vs New York New York’s finance-sector ML roles (Two Sigma, Citadel, Renaissance) pay exceptionally well — often matching or exceeding FAANG. For ML engineers interested in financial modeling or algorithmic trading, NYC is competitive. For ML engineers in tech, Seattle offers comparable pay with a lower cost of living. Seattle vs Remote Many elite remote ML roles pay $140K–$200K with no location adjustment. For senior ML engineers, being in Seattle gives access to in-person collaboration with world-class teams — which matters for career velocity and promotion speed at companies with in-person cultures like Amazon. Read our full ML engineer salary guide across all cities →

Negotiation Tips for Seattle ML Engineers

Understand the RSU structure before negotiating. Amazon’s RSUs vest on a back-weighted schedule (5%/15%/40%/40%). If you’re mid-vesting at your current employer, negotiate a sign-on bonus to cover your unvested equity — a completely standard ask that can add $30K–$80K to year-one compensation. Specify your ML specialization explicitly. “Machine learning engineer” is a broad category. If you have LLM fine-tuning experience, production MLOps expertise, or distributed training at scale, make this central to your narrative. These specializations justify above-band offers. Counter with total comp, not just base. Amazon and Meta negotiate heavily on RSUs. Getting an additional $30K–$50K in RSUs vs an additional $10K in base is almost always financially superior over a 4-year vesting period. Leverage competing offers. Seattle’s ML market is competitive enough that having two offers from Amazon, Microsoft, Google, or Meta is realistic for senior engineers. Competing offers are the most reliable mechanism for negotiating above standard band — and Seattle employers expect this. Use certifications as anchors. AWS Machine Learning Specialty, Google Professional ML Engineer, or a recent NeurIPS/ICML publication can justify above-band compensation and are faster to obtain or cite than most candidates realize.

Is Seattle the Right ML Market for You?

Seattle is the right choice for ML engineers who want to maximize total take-home compensation while working on high-scale, real-world ML systems. The concentration of Amazon, Microsoft, Meta, Google, and AI2 in a single metro area creates both exceptional career optionality and genuine salary competition.

The trade-offs: Amazon’s culture is demanding. Seattle’s weather is famously gray. Housing costs have risen substantially. But for ML engineers optimizing for financial outcomes over 5–10 years, the mathematics favor Seattle clearly over San Francisco, New York, or any other US market.

Take the CareerCheck career quiz to see if Seattle is right for your ML career → Compare software engineer salaries in Seattle →

Use CareerCheck’s Seattle ML engineer salary tool to benchmark your current or target compensation against live market data — and find out whether it’s time to negotiate, move, or make your next career move.