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Overnight Machine Learning Quant Jobs in Seattle, WA

Senior Machine Learning Engineer

Seattle, WA

$118K - $163K/yr

Master's degree or PhD in Mathematics, Statistics, Machine Learning or related quantitative field (or equivalent experience). * 8+ years experience applying Machine Learning to operational systems.

New

Machine Learning Engineer II

Seattle, WA · On-site

$111K - $151K/yr

You have a demonstrated track record in one or more machine learning subfield relevant to financial modeling, such as time series analysis, quantitative modeling, optimization, anomaly detection, or ...

AI Engineer - Machine Learning 3

Redmond, WA · Remote

$117K - $140K/yr

Machine Learning Data Scientist - Research Translation & Prototypin Top 3 Must-Have HARD Skills ... Design and execute quantitative and qualitative experiments that measure model performance, user ...

... related quantitative field. Join us at Adobe and help compose the future of creative content ... machine learning. Together, we'll develop groundbreaking solutions that empower creatives around ...

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Showing results 1-20

Overnight Machine Learning Quant information

See Seattle, WA salary details

$59.7K

$135.6K

$223.6K

How much do overnight machine learning quant jobs pay per year?

As of Aug 6, 2026, the average yearly pay for overnight machine learning quant in Seattle, WA is $135,613.00, according to ZipRecruiter salary data. Most workers in this role earn between $89,300.00 and $173,500.00 per year, depending on experience, location, and employer.

What is the difference between Overnight Machine Learning Quant vs Quantitative Researcher?

AspectOvernight Machine Learning QuantQuantitative Researcher
CredentialsAdvanced degrees in CS, Math, or Stats; programming skillsSimilar; advanced degrees often required
Work EnvironmentFinancial firms, hedge funds, trading desks; fast-paced, data-drivenFinancial institutions, research labs; analytical, research-focused
Industry UsageHigh-frequency trading, algorithmic strategiesMarket analysis, model development
Work HoursOvernight shifts aligned with trading hoursStandard business hours, flexible in some cases

While both roles involve quantitative analysis and programming, Overnight Machine Learning Quants focus on developing models for overnight trading strategies, often working overnight shifts. Quantitative Researchers typically conduct broader market research and model development during regular hours. The roles overlap in skills but differ mainly in work hours and specific application areas.

Senior Machine Learning Engineer

Nvidia

Seattle, WA

$118K - $163K/yr

Full-time

Posted 3 days ago

New


Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

8th of 242 rated software companies


Job description

As a Senior Machine Learning Engineer at NVIDIA, you will build the machine learning brain that keeps NVIDIA's global DGX Cloud healthy, efficient and ready for the next waves of AI breakthroughs. DGX Cloud fuses NVIDIA GPUs, NVLink networking and the full AI software stack into elastic infrastructure powering large language models, drug discovery, autonomous driving and climate science. Your models will turn billions of telemetry signals into predictive insight. This frees customers to innovate while our platform runs smarter.

What you'll be doing:

  • Ground breaking and developing innovative machine learning algorithms and models that propel our AI products.

  • Build production models for anomaly detection, predictive maintenance and usage optimization.

  • Develop tools surfacing real time telemetry, efficiency metrics and long term trends.

  • Develop forecasting and simulation models for global scale planning.

  • Analyzing complex datasets to determine the best approach for model training and optimization.

  • Translate findings into clear engineering actions with infrastructure, operations and product teams.

  • Participating in cross-functional projects to integrate machine learning capabilities into various NVIDIA products.

What we need to see:

  • Master's degree or PhD in Mathematics, Statistics, Machine Learning or related quantitative field (or equivalent experience).

  • 8+ years experience applying Machine Learning to operational systems.

  • Proven track record of building and deploying Machine Learning models in production environments.

  • Experience with time series analysis and optimization algorithms.

  • Familiarity with distributed systems and cloud platforms such as AWS and Kubernetes.

  • Strong software engineering skills and proficiency in Python.

  • Effective verbal/written communication, and technical presentation skills.

  • Experience with machine learning frameworks such as TensorFlow, PyTorch, or similar.

  • A track record of delivering high-impact projects to compete in a fast-paced environment.

Ways to stand out from the crowd:

  • Experience solving capacity planning problems.

  • Deep understanding of GPU performance metrics.

  • Familiarity with prometheus and PromQL.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until August 7, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

What Nvidia employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


Nvidia logo

About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

Year founded

1993