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Remote Generative Ai Engineer Jobs in Federal Way, WA

Remote Job Overview We are seeking experienced AI Consulting Domain Experts to contribute their ... Prompt Engineering * AI Output Evaluation * Quality Assurance * Technical & Report Writing

Remote Job Overview We are seeking experienced AI Consulting Domain Experts to contribute their ... Prompt Engineering * AI Output Evaluation * Quality Assurance * Technical & Report Writing

Experience building or managing AI-powered, generative AI, or agentic products. * Working knowledge ... and DevOps or site reliability engineering practices. * Familiarity with metrics, logs, traces ...

AI Agentic Engineer

Seattle, WA · On-site +1

$60 - $82.25/hr

What you'll do As an AI Agentic Engineer on the Platform AI Engineering team, you will drive the ... Employee divides their time between in-office and remote work. Access to an office location is ...

... generative AI systems. Software Engineer, Systems ML Engineering Responsibilities: * Design and implement scalable ML systems infrastructure components, including distributed training frameworks ...

Sr. Product Manager, Enterprise AI

Seattle, WA · Remote

$144K - $190K/yr

This is a remote opportunity, but applicants must reside in the greater Seattle area. ESSENTIAL ... generative-AI tooling (e.g., prompt engineering, retrieval-augmented generation), and data ...

Showing results 21-40

Remote Generative Ai Engineer information

See Federal Way, WA salary details

$42.4K

$129.4K

$213.9K

How much do remote generative ai engineer jobs pay per year?

As of Aug 20, 2026, the average yearly pay for remote generative ai engineer in Federal Way, WA is $129,390.00, according to ZipRecruiter salary data. Most workers in this role earn between $92,700.00 and $169,200.00 per year, depending on experience, location, and employer.

What is a remote generative AI engineer?

A Remote Generative AI Engineer is a technology professional who specializes in developing, training, and deploying artificial intelligence models that can generate new content—such as text, images, audio, or video—while working from a remote location. These engineers typically work with advanced machine learning techniques like deep learning, neural networks, and large language models. Their responsibilities often include designing algorithms, optimizing model performance, and collaborating with distributed teams to build innovative AI-driven solutions. The remote aspect allows them to perform their duties from anywhere with internet access, offering flexibility and access to global opportunities.

What are the key skills and qualifications needed to thrive as a remote generative AI engineer?

To thrive as a Remote Generative AI Engineer, you need a solid background in computer science, machine learning, and deep learning, typically with a relevant degree and experience in building AI models. Familiarity with frameworks like TensorFlow or PyTorch, cloud platforms (such as AWS or Azure), and version control systems like Git is essential. Strong problem-solving, self-motivation, and effective remote communication set outstanding engineers apart in this role. These skills are crucial for developing innovative AI solutions, collaborating across distributed teams, and delivering impactful results in a remote work environment.

How do remote generative AI engineers typically collaborate with cross-functional teams to deliver AI-driven solutions?

Remote Generative AI Engineers often work closely with data scientists, product managers, and software engineers to integrate generative AI models into products or services. Collaboration is usually facilitated through virtual meetings, code repositories, and project management tools, enabling seamless communication across different time zones. Regular check-ins and sprint reviews help ensure alignment on goals, while documentation and clear communication are essential for maintaining project momentum. This collaborative environment not only fosters innovation but also allows engineers to gain exposure to a variety of perspectives and expertise.

What is the difference between Remote Generative Ai Engineer vs Remote Machine Learning Engineer?

AspectRemote Generative Ai EngineerRemote Machine Learning Engineer
Required CredentialsBachelor's or higher in CS, AI, or related; experience with generative modelsBachelor's or higher in CS, Data Science, or related; experience with ML algorithms
Work EnvironmentCollaborates on AI model development, focuses on generative models like GPT, GANsDevelops and deploys ML models for various applications, including predictive analytics
Employer & Industry UsageTech companies, AI startups, research institutionsTech firms, finance, healthcare, and data-driven industries

While both roles involve AI and machine learning, a Remote Generative Ai Engineer specializes in creating models that generate content, such as text or images, using generative techniques. In contrast, a Remote Machine Learning Engineer works on a broader range of ML models for predictive or classification tasks. The roles often overlap but differ in focus and application.

How much does a remote generative AI engineer make?

A remote generative AI engineer typically earns between $100,000 and $160,000 annually, depending on experience, skills, and the company's location. Senior roles or those with specialized expertise in machine learning and deep learning can command higher salaries, especially with proficiency in tools like TensorFlow or PyTorch.

What are the best remote generative AI engineer jobs?

Remote generative AI engineer jobs are available across technology companies, research institutions, and startups, often requiring skills in machine learning frameworks like TensorFlow or PyTorch and experience with natural language processing or computer vision. These roles typically involve developing and deploying AI models remotely, with some positions offering flexible schedules and requiring certifications or advanced degrees in computer science or related fields.

What is the average salary of a remote generative AI engineer?

The average salary for a remote generative AI engineer typically ranges from $100,000 to $150,000 annually, depending on experience, skills in machine learning frameworks, and the complexity of projects. Senior roles or those with specialized expertise in deep learning and large language models can earn higher compensation. Remote positions often offer competitive pay comparable to on-site roles in the tech industry.

What job categories do people searching Remote Generative Ai Engineer jobs in Federal Way, WA look for?

The top searched job categories for Remote Generative Ai Engineer jobs in Federal Way, WA are:

What cities near Federal Way, WA are hiring for Remote Generative Ai Engineer jobs?

Cities near Federal Way, WA with the most Remote Generative Ai Engineer job openings:

Technical Marketing Engineer and Writer

Hedgehog

Seattle, WA • Remote

Full-time

Medical, Dental, Vision

Re-posted 7 days ago


Job description

Company Description

About Hedgehog

AI needs a new network.  Hedgehog is the AI network.  AI developers need new cloud infrastructure with high performance compute that trains and tunes generative AI models quickly and efficiently.  They need ultra-low latency for AI inference so users get a human experience. Traditional cloud networks lack the congestion control and adaptive routing required to minimize AI job completion time.  AI cloud builders find current reference architectures expensive and difficult to operate because they require specialized network engineers from a very limited number of vendors.  Hedgehog delivers a high performance AI network that reduces AI job completion time up to 35% with flow scheduling and buffer management for congestion control and adaptive routing.  Our low latency cloud network is multi-tenant for so that many teams can tune models, and many people can use model.  A Hedgehog cloud network is easy to operate.  If you know how to use AWS, Azure to Google Cloud, you can run a Hedgehog cloud.  And you can build a Hedgehog AI cloud at reasonable cost with open source software, white box hardware from a wide selection of vendors, and fully automated operations with your existing team.  

    Job Description

    Want to show the world how to build AI infrastructure?  Want to guide new cloud builders on how to design, build and operate AI cloud networks?  Better yet, want to build an AI assistant that does this for you?  If you have a network engineering background and you enjoy telling good stories while documenting and demonstrating technology, this is the job for you.  

    As Hedgehog's first Technical Marketing Engineer, you will play a key role in defining this critical job function at a fast growing open source company leading the AI Network category.  In the short term you will:

    Explain the Hedgehog product producing 2-3 minute YouTube videos covering a range of topics including:

    • Hedgehog Virtual Private Cloud service
    • Hedgehog Control Plane
    • Hedgehog Data Plane
    • Hedgehog Zero Touch Provisioning
    • Hedgehog Network Observability
    • Hedgehog Network Troubleshooting
    • Hedgehog Software Updates

    Demonstrate the Hedgehog product live for prospective customers.

    Wear a second hat as a technical writer improving technical documentation from our engineering team.  Improvements include tech writing best practices for a quick start guide, tutorials, lab exercises, background information, glossary, and context that frames the software engineering details. 

    Train a Hedgehog virtual assistant to answer customer questions by feeding your technical documentation and marketing material into Retrieval Augmented Generation (RAG) for an open source Large Language Model (LLM).

    Guide prospective customers through virtual lab exercises so they can evaluate the same product features that you demonstrate in videos and discovery calls.  

    Assist prospective customers in designing, planning and scoping their AI cloud infrastructure. 

    Assist prospective customers in documenting their infrastructure as code, implementing Gitops, and integrating Hedgehog into their Gitops process.  

    Position Hedgehog relative to our partners and competitors.  

    Handle customer objections and build objection handling playbooks for SDRs using Hubspot.

    Write blogs on AI network topics, Hedgehog capabilities, and Hedgehog customer stories.

    Train new sellers at Hedgehog and our GTM partners on how to position Hedgehog in AI cloud infrastructure solutions.  

    Qualifications

    Requirements:

    • Bachelor's or Graduate's Degree in computer science, data science, electronics, or engineering.

    • Industry experience with cloud networking and/or a strong understanding of cloud networking concepts like VPC, BGP EVPN, VXLAN, NAT, DHCP, ZTP, SDN, RoCEv2, ECN, PFC

    • Strong technical writing skills demonstrated by a reference portfolio

    • Strong oral communication with a gift to simply explain complex technical concepts with stories that non-technical people can easily understand

    • Basic video editing skills 

    Bonus:

    • Degree (or equivalent) in Computer Science, Computer Engineering, or a related technical field

    • Curious nature and desire to tinker: you want to pull things apart to see how they work

    • Love of new and emerging technologies

    • Ability to distill complicated ideas to just the right number of words

    • Experienced with technical writing using Markdown and Material for MkDocs

    • Experience with AI/ML models

    • Experience with open source software

    • Experience in embedded or network engineering, technical support, product testing, or QA

    Additional Information

    Hedgehog Benefits

    • World-class team
    • Fun culture
    • Engaging and interesting engineering problems
    • Competitive salary
    • Startup equity
    • Health Insurance (Medical, Dental, Vision)
    • Unlimited time off
    • Work from home (fully remote - we don't care where you are; we care about what you can do)
    • Laptop, IT equipment