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Remote Machine Learning Compiler Engineer Jobs in Seattle, WA

Truveta

ML PhD Intern - LLMs & Generative AI

Seattle, WA · Remote

... remote Who We Need We are seeking a highly motivated and talented Machine Learning PhD Intern to ... Collaborate with researchers and engineers to design, develop, and refine large language models and ...

Aquent

Software Development Engineer 1

Redmond, WA · On-site +1

$39 - $44/hr

Contributing to projects involving machine learning models and data science activities. * Engaging ... Strong software engineering skills, including proficiency in coding and development. * Basic ...

Wsgr

Innovations and AI Solutions Engineer

Seattle, WA · On-site +1

This position is available as a hybrid or remote work schedule. Essential Duties, Responsibilities ... Design, build and implement machine learning models, including the development of AI Models and ...

Nintendo

Engineer (NTD)

Redmond, WA · On-site +1

Significant experience with modern machine learning, frameworks, and Python. * Practical experience ... This position is onsite in Redmond, WA, and not open to remote status at this time.

iSpot

Research Data Scientist 1

Bellevue, WA · Remote

$95K - $106K/yr

... engineering teams to scale our models to satisfy the needs of brands, publishers, networks, and ... Machine Learning Model Development: Develop, train, and deploy state-of-the-art machine learning ...

Databricks

Senior Software Engineer - Backend

Bellevue, WA · On-site +1

$138K - $182K/yr

Founded by engineers - and customer obsessed - we leap at every opportunity to solve technical ... Build Databricks serverless platform that powers the big data, machine learning and Gen AI ...

Paradigm

Senior Applied ML Engineer

Seattle, WA · Remote

$125K - $183K/yr

We are looking for a Senior Applied ML Engineer to design, implement, and scale machine learning systems that power next-generation construction and digital twin solutions. You will apply advanced ML ...

Uber

Staff Software Engineer

Seattle, WA · On-site +1

This role is ideal for a strong software engineer with a machine learning background who is excited to apply ML/GenAI techniques to real-world security problems at scale.The security landscape ...

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Remote Machine Learning Compiler Engineer information

See Seattle, WA salary details

$85.4K

$190.5K

$233.3K

How much do remote machine learning compiler engineer jobs pay per year?

As of Jul 9, 2026, the average yearly pay for remote machine learning compiler engineer in Seattle, WA is $190,548.00, according to ZipRecruiter salary data. Most workers in this role earn between $162,700.00 and $233,300.00 per year, depending on experience, location, and employer.

How does a Remote Machine Learning Compiler Engineer typically collaborate with cross-functional teams to optimize model deployment?

As a Remote Machine Learning Compiler Engineer, you will frequently collaborate with data scientists, hardware engineers, and software developers to ensure that machine learning models are efficiently compiled and deployed on target platforms. Communication often takes place through virtual meetings, code reviews, and shared documentation tools. You'll be responsible for translating research models into optimized code, troubleshooting performance bottlenecks, and integrating feedback from various stakeholders. Effective teamwork is crucial, as the success of deployments often depends on iterative feedback and close alignment with both the ML research and hardware teams.

What is a Remote Machine Learning Compiler Engineer?

A Remote Machine Learning Compiler Engineer is a software engineer who specializes in developing and optimizing compilers specifically for machine learning workloads, while working from a remote location. Their primary responsibilities include designing and implementing compiler features that translate machine learning models into efficient code for various hardware platforms, such as CPUs, GPUs, or specialized accelerators. They collaborate closely with machine learning researchers, hardware engineers, and software developers to ensure high performance and compatibility. In addition to strong programming skills, they typically require expertise in compiler theory, machine learning frameworks, and hardware architectures. This role allows for flexible, location-independent work while contributing to cutting-edge AI technologies.

What is the difference between Remote Machine Learning Compiler Engineer vs Remote Data Scientist?

AspectRemote Machine Learning Compiler EngineerRemote Data Scientist
Required CredentialsBachelor's or Master's in Computer Science, Software Engineering, or related fields; knowledge of compiler design and ML frameworksBachelor's or Master's in Data Science, Statistics, or related fields; proficiency in programming, statistics, and data analysis
Work EnvironmentPrimarily software development, compiler optimization, and ML model deploymentData analysis, model building, and interpretation of results
Industry UsageTech companies, AI startups, hardware firms focusing on ML hardware accelerationTech, finance, healthcare, and research organizations

While both roles involve working with machine learning, the Remote Machine Learning Compiler Engineer focuses on developing and optimizing compilers for ML models, whereas the Remote Data Scientist concentrates on analyzing data and building predictive models. The roles share some technical skills but differ in their core responsibilities and work environments.

What are the key skills and qualifications needed to thrive as a Remote Machine Learning Compiler Engineer, and why are they important?

To thrive as a Remote Machine Learning Compiler Engineer, you need a strong background in computer science, proficiency in programming languages like C++ and Python, and expertise in compiler theory and machine learning frameworks. Familiarity with ML compilers such as TVM or XLA, and experience using version control and CI/CD systems are commonly required, along with a relevant bachelor's or master's degree. Outstanding problem-solving, collaboration, and communication skills are essential for working effectively in distributed teams and across technical domains. These skills and qualities enable the development of efficient, scalable ML solutions that bridge software and hardware, ensuring high performance and innovation.
What are the most commonly searched types of Machine Learning Compiler Engineer jobs in Seattle, WA? The most popular types of Machine Learning Compiler Engineer jobs in Seattle, WA are:
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Remote Machine Learning Compiler Engineer jobs near you
Distinguished Machine Learning Engineer

Distinguished Machine Learning Engineer

Geico

Seattle, WA • On-site, Remote

Full-time

Re-posted 5 days ago

GEICO rating

8.0

Company rating: 8.0 out of 10

Based on 354 frontline employees who took The Breakroom Quiz

143rd of 278 rated insurance

Job description

Why Join GEICO?

At GEICO, we offer a rewarding career where your ambitions are met with endless possibilities.

Every day we honor our iconic brand by offering quality coverage to millions of customers and being there when they need us most. We thrive on relentless innovation to exceed our customers' expectations while making a real impact on local communities nationwide.

Founded in 1936, GEICO is a member of the Berkshire Hathaway family of companies and one of the largest auto insurers in the United States. When you join our company, we want you to feel valued, supported, and proud to work here. That's why we offer the GEICO Pledge: Great Company, Great Culture, Great Rewards, and Great Careers.

Distinguished Engineer

GEICO is seeking a Distinguished Engineer (AI Platforms) to join our AI organization. This individual will serve as one of the most senior technical authorities driving the architecture, evolution, and long-term technical strategy of GEICO's Generative AI and virtual agent platforms. This platform directly supports productivity and service quality for 20K+ contact center employees across claims, service, and sales.

In this role, you willoperatewith enterprise-wide technical influence, shaping foundational AI platform capabilities that enable large-scale, production-grade GenAI and agentic workflows across GEICO. You will work closely with senior engineers, architects, product leaders, and executives to define and evolve durable, scalable, and extensible AI systems that underpin multiple lines of business.

The ideal candidate brings a proventrack recordof designing and architecting complex, multi-system AI/ML platforms at scale, deep hands-onexpertise, and a strong passion for Generative AI technologies in real-world production environments.

Key Responsibilities

Enterprise Architecture & Technical Authority

  • Define, own, and evolve the foundational architecture for GEICO's Generative AI and agentic workflow platforms.

  • Serve as a final technical authority on complex architectural decisionsimpactingmultiple products, teams, and business domains.

  • Design interconnected, high-performance, and durable platform components that power end-to-end GenAI workflows, including:

  • Knowledge curation and management

  • Search and retrieval systems

  • Prompt and context management

  • Workflow orchestration and action execution

  • Semantic and knowledge graph systems

Platform & GenAI Applications Strategy, Architecture, and Business Impact

  • Establish and drive multi-year technical strategy and roadmaps for both AI platform capabilities and Generative AI (GenAI) applications in close partnership with product and business leaders.

  • Balance speed, scalability, reliability, and extensibility while ensuring platforms and GenAI applications can support future AI use cases, evolving business needs, and organizational growth.

  • Influence investment decisions by evaluating build vs. buy tradeoffs and architectural choices for both the underlying platform and GenAI applications.

  • Define the reference architecture and best practices for GenAI application development, deployment, and integration, ensuring alignment with overall enterprise architecture.

  • Collaborate with business stakeholders toidentifyhigh-impact GenAI application opportunities and develop strategies to maximize business value and measurable outcomes.

  • Continuously assess and communicate the business impact of GenAI applications, providing clear metrics and feedback loops to inform ongoing strategy and platform evolution.

System & Technology Evaluation

  • Lead evaluation and selection of core technologies, frameworks, and infrastructure componentswithaemphasis on building andscalingGenerativeAI applications, including LLM orchestration(e.g.,LangChain,LlamaIndex), agenticworkflows, RAG systems, andevaluation/observability tooling, while partnering on underling AI platform infrastructure and services to support production readiness.

  • Ensure architectural consistency and technical rigor across open-source, cloud-agnostic, and managed service integrations.

Cross-Organization Influence

  • Collaborate across engineering, data science, ML, product, and design organizations to align on platform and GenAI application direction, technical standards, and businessobjectives.

  • Drive alignment across teams by translating complex technical and business concepts into clear architectural guidance and decision frameworks.

  • Partner with senior technical and business leaders across departments to promote enterprise-wide adoption of GenAI best practices and maximize organizational impact.

Technical Leadership & Problem Solving

  • Tackle the most complex and ambiguous technical and business challenges affecting system-wide and application-specific performance, reliability, and scalability.

  • Lead deep technical reviews, architectural assessments, and design discussions for critical AI and GenAI application initiatives.

  • Guideplatform and GenAI application evolution through hands-onengagementwhen necessary, especially in high-impact or high-risk areas.

Mentorship & Technical Stewardship

  • Mentor senior engineers and technical leads, setting a high bar for architectural thinking, engineering quality, and technical decision-making for both platform and GenAI application initiatives.

  • Establish and reinforce best practices for platform and GenAI application design, reliability, observability, and operational excellence.

  • Contribute to internal documentation, architectural standards, and technical knowledge sharing for both the AI platform and GenAI applications.

Minimum Qualifications

  • Master's degree or higher in Computer Science, Engineering, Statistics, ora relatedfield.

  • 10+ years of professional software engineering experience, with deepexpertisein large-scale distributed systems.

  • Extensive experience architecting and building multi-componentAI/ML platforms using technologies such as:

  • Search and retrieval systems (e.g., Elasticsearch,Qdrant, Milvus,Pinecone,Weaviate)

  • Data platforms (e.g., Snowflake, relational and NoSQL databases, and feature stores)

  • Streaming and distributed processing (e.g., Kafka, Spark, Ray)

  • Workflow orchestration (e.g., Airflow, Temporal, Prefect)

  • LLM orchestration and application frameworks( e.g.,LangChain,Llamaindex)

  • Observability, evaluation, and tracing for GenAI systems (e.g.,LangSmith,ArizePhoenix, Weights & Biases,OpenTelemetry)

  • Vector databases, embedding pipelines,and retrieval-augmented generation (RAG) architectures

  • Agenticframeworksand multi-agent systems for complex task execution

  • Strong background in full software development lifecycle ownership, including CI/CD, Kubernetes, monitoring, and production operations.

  • Deep experience with major cloud platforms such as AWS and Azure.

  • Demonstrated hands-on experience building production systems using LLMs and Generative AI technologies (e.g., GPT, Llama, Mistral, Claude) to power conversational and agentic workflows.


Annual Salary

$210,000.00 - $350,000.00

The above annual salary range is a general guideline. Multiple factors are taken into consideration to arrive at the final hourly rate/ annual salary to be offered to the selected candidate. Factors include, but are not limited to, the scope and responsibilities of the role, the selected candidate's work experience, education and training, the work location as well as market and business considerations.


At this time, GEICO will not sponsor a new applicant for employment authorization for this position.

The GEICO Pledge:

Great Company:Protecting customers through life's twists and turns with innovation and integrity.

Great Careers:Personalized development programs, mentorship, and certification assistance.

Great Culture:Inclusive and collaborative culture rooted in shared success.

Great Rewards:Competitive pay, benefits, and flexibility to support your well-being and future.

The equal employment opportunity policy of the GEICO Companies provides for a fair and equal employment opportunity for all associates and job applicants regardless of race, color, religious creed, national origin, ancestry, age, gender, pregnancy, sexual orientation, gender identity, marital status, familial status, disability or genetic information, in compliance with applicable federal, state and local law. GEICO hires and promotes individuals solely on the basis of their qualifications for the job to be filled.

GEICO reasonably accommodates qualified individuals with disabilities to enable them to receive equal employment opportunity and/or perform the essential functions of the job, unless the accommodation would impose an undue hardship to the Company. This applies to all applicants and associates. GEICO also provides a work environment in which each associate is able to be productive and work to the best of their ability. We do not condone or tolerate an atmosphere of intimidation or harassment. We expect and require the cooperation of all associates in maintaining an atmosphere free from discrimination and harassment with mutual respect by and for all associates and applicants.

What GEICO employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

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About GEICO

Sourced by ZipRecruiter

GEICO is built on ingenuity, perseverance, innovation, resilience, and hard, honest work. From its humble beginnings in the midst of the Great Depression to its current place as one of the most successful companies in the nation, GEICO represents a quintessential American success story. At GEICO, we love that our associates are proud goal-seekers, and that's why we believe in celebrating their milestones and rewarding their achievements. Throughout the year we reward performance and accomplishments, host programs that recognize personal successes, and acknowledge innovation, service, and leadership.

Industry

Insurance services

Company size

10,000+ Employees

Headquarters location

Chevy Chase, MD, US

Year founded

1936

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