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Data Engineer Ml Jobs in Seattle, WA (NOW HIRING)

Scale AI

ML Research Engineer, ML Systems

Seattle, WA · On-site

The ML Research Engineer will build and optimize the internal distributed framework for large ... and data curation • Research and integrate state-of-the-art technologies to optimize our ML ...

Vibotek LLC

Data Engineer

Seattle, WA

$130K - $156K/yr

The Data Engineer will be responsible for designing, building, and maintaining robust and scalable ... ML. * Design simple, reusable data models to support training and inference. * Implement data ...

CyberProof

Associate Data Engineer

Seattle, WA · On-site

$130K - $156K/yr

... ML workloads. • Azure certifications (Azure Fundamentals, Data Engineer Associate) or working toward them. • Familiarity with data privacy concepts (GDPR, CCPA) and HR data handling ...

LVT

Staff Data Engineer

Seattle, WA

You will partner closely with AI/ML research, the ML platform / MLOps function. You own the data ... Set the data-engineering standards for the flywheel schema conventions, dataset contracts, quality ...

PitchBook Data

Lead Data Engineer

Seattle, WA · On-site

$130K - $156K/yr

Act as a technical mentor and coach a team of data engineers with diverse experience levels ... Experience applying AI/ML or automation techniques to improve operational efficiency * Must be ...

Vibotek LLC

Data Engineer

Seattle, WA · On-site

$130K - $156K/yr

Vibotek LLC is a technology company seeking a Data Engineer. The role involves ingesting and ... AI/ML. • Design simple, reusable data models to support training and inference. • Implement ...

PitchBook Data

Lead Data Engineer

Seattle, WA · On-site

$130K - $156K/yr

Act as a technical mentor and coach a team of data engineers with diverse experience levels ... Experience applying AI/ML or automation techniques to improve operational efficiency * Must be ...

Team Red Dog

AI Data Engineer 3

Redmond, WA · On-site

$128K - $154K/yr

This opportunity is expected to focus on enterprise data engineering, cloud-based analytics infrastructure, ETL/ELT development, and AI/ML-driven data initiatives supporting large-scale business ...

Ampcus Inc

Data Engineer IV

Seattle, WA · On-site

$130K - $156K/yr

We are looking for a Data Engineer to join the Infrastructure Automation team, responsible for ... ML,digital solutions, Cybersecurity & Risk management, Testing, Forensics & Fraud services and ...

Outpost

Machine Learning Data Engineer

Seattle, WA · Remote

$130K - $160K/yr

Curate, label, and prioritize datasets for model retraining, partnering closely with our ML and CV ... Qualifications: * 3+ years in a data quality, ML data engineering or applied ML role. * Experience ...

Outpost

Machine Learning Data Engineer

Seattle, WA · On-site

$130 - $160/hr

Curate, label, and prioritize datasets for model retraining, partnering closely with our ML and CV ... Qualifications: * 3+ years in a data quality, ML data engineering or applied ML role. * Experience ...

Amazon

Data Engineer II, Intl. Seller Services

Seattle, WA · On-site

$130K - $156K/yr

ISS is seeking a highly motivated, experienced Data Engineer to help design and build the next generation of Data and ML infrastructure to power GenAI applications. We are a team of Data Engineers ...

eTeam

AI & Data - Data Engineer

Seattle, WA · On-site

$130K - $156K/yr

Job Summary : eTeam is looking for a Data Engineer specializing in AI and Data. The role involves ... AI/ML. • Design simple, reusable data models to support training and inference. • Implement ...

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All JobsData Engineer Ml JobsData Engineer Ml Jobs in Seattle, WA

Data Engineer Ml information

See Seattle, WA salary details

$52.3K

$187.8K

$277.1K

How much do data engineer ml jobs pay per year?

As of Aug 24, 2026, the average yearly pay for data engineer ml in Seattle, WA is $187,795.00, according to ZipRecruiter salary data. Most workers in this role earn between $151,900.00 and $193,500.00 per year, depending on experience, location, and employer.

What does a data engineer ML do?

A Data Engineer ML (Machine Learning) is responsible for designing, building, and maintaining the data pipelines and infrastructure necessary for machine learning applications. They clean, process, and organize large datasets to ensure data quality and accessibility for data scientists and ML engineers. In addition, they may work on deploying machine learning models to production environments and optimizing data workflows for efficiency and scalability.

What are the key skills and qualifications needed to thrive as a data engineer ML?

To thrive as a Data Engineer ML, you need strong programming skills (especially in Python or Scala), knowledge of data modeling, and a solid foundation in database technologies, typically supported by a degree in computer science or a related field. Familiarity with big data frameworks (like Spark or Hadoop), cloud platforms (AWS, GCP, or Azure), and ETL tools, as well as relevant certifications, is highly beneficial. Excellent problem-solving abilities, teamwork, and clear communication help you collaborate with data scientists and stakeholders effectively. These skills are essential for building robust data pipelines and infrastructure that enable scalable, high-quality machine learning solutions.

How do data engineer ML roles typically collaborate with data scientists and machine learning engineers on projects?

Data Engineer ML professionals work closely with data scientists and machine learning engineers by building and maintaining robust data pipelines, ensuring clean and reliable datasets are readily available for modeling and analysis. They often participate in meetings to understand model requirements, help optimize data storage for performance, and support the deployment of machine learning models into production environments. Effective collaboration involves continuous communication to troubleshoot data issues, implement data validation, and scale solutions as project needs evolve. This teamwork ensures that data-driven projects move efficiently from experimentation to deployment.

What is the difference between Data Engineer Ml vs Data Scientist?

AspectData Engineer MlData Scientist
Required CredentialsBachelor's in CS, Data Engineering certificationsBachelor's/Master's in CS, Data Science certifications
Work EnvironmentBuilding data pipelines, managing databasesAnalyzing data, creating models
Employer & Industry UsageTech companies, finance, healthcareResearch institutions, tech firms, finance

Data Engineer Ml focuses on developing and maintaining data infrastructure and pipelines, while Data Scientists analyze data and build predictive models. Both roles often collaborate but serve different functions within data teams.

What are popular job titles related to Data Engineer Ml jobs in Seattle, WA?

For Data Engineer Ml jobs in Seattle, WA, the most frequently searched job titles are:

What job categories do people searching Data Engineer Ml jobs in Seattle, WA look for?

The top searched job categories for Data Engineer Ml jobs in Seattle, WA are:

What cities near Seattle, WA are hiring for Data Engineer Ml jobs?

Cities near Seattle, WA with the most Data Engineer Ml job openings:

Data Engineer Ml jobs near you
Infographic showing various Data Engineer Ml job openings in Seattle, WA as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 12% Part Time, and 4% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $187,795 per year, or $90.3 per hour.

ML Research Engineer, ML Systems

Scale AI

Seattle, WA • On-site

Full-time

Re-posted 5 days ago

Scale AI rating

8.5

Company rating: 8.5 out of 10

Based on 9 frontline employees who took The Breakroom Quiz

80th of 246 rated software companies

Job description

Job Summary:
Scale AI is a company focused on developing reliable AI systems for critical decisions. The ML Research Engineer will build and optimize the internal distributed framework for large language model training and inference, collaborating with various ML teams to support research and development efforts.
Responsibilities:
• Build, profile and optimize our training and inference framework
• Collaborate with ML teams to accelerate their research and development and enable them to develop the next generation of models and data curation
• Research and integrate state-of-the-art technologies to optimize our ML system
Qualifications:
Required:
• Strong excitement about system optimization
• Experience with multi-node LLM training and inference
• Experience with developing large-scale distributed ML systems
• Strong software engineering skills, proficient in frameworks and tools such as CUDA, Pytorch, transformers, flash attention, etc.
• Strong written and verbal communication skills and the ability to operate in a cross functional team environment
Preferred:
• Demonstrated expertise in post-training methods &/or next generation use cases for large language models including instruction tuning, RLHF, tool use, reasoning, agents, and multimodal, etc.
Company:
Scale’s mission is to develop reliable AI systems for the world’s most important decisions. Founded in 2016, the company is headquartered in San Francisco, USA, with a team of 501-1000 employees. The company is currently Late Stage.

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