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Machine Learning Infrastructure Engineer Jobs in Seattle, WA

We're looking for an exceptional Machine Learning Engineer to help shape the future of our core platforms, products, and customer experiences. FinTech is one of the most complex and rapidly evolving ...

Machine Learning Engineer

Seattle, WA ยท On-site

$120K - $180K/yr

Machine Learning Role In order to execute our vision, we need to grow our team of best-in-class machine learning engineers. We are looking for developers who are excited about staying at the ...

Machine Learning Engineer

Seattle, WA ยท On-site

$120K - $180K/yr

Machine Learning Role In order to execute our vision, we need to grow our team of best-in-class machine learning engineers. We are looking for developers who are excited about staying at the ...

Description Apple's Video Computer Vision (VCV) Face and Body technologies team is looking for a skilled Machine Learning Engineer with experience developing ML models for computer vision and ...

Applied Machine Learning Engineer responsibilities include creating machine learning models and retraining systems. To do this job successfully, you need exceptional skills in statistics and ...

Applied Machine Learning Engineer responsibilities include creating machine learning models and retraining systems. To do this job successfully, you need exceptional skills in statistics and ...

Senior Machine Learning Engineer

Seattle, WA ยท On-site

$139K - $183K/yr

As a Machine Learning Engineer at Axon , you'll help build AI solutions that are transforming ... Architect and develop the infrastructure needed to train, evaluate, deploy, monitor, and ...

Senior Cloud Infrastructure Engineer

Seattle, WA ยท On-site

$123K - $167K/yr

... Engineer - Infrastructure, you will design, build, and operate scalable, cost-efficient cloud ... machine learning workloads, data systems, and production services. You will help ensure our ...

As a Machine Learning Engineer II, you will be a key contributor throughout the machine learning lifecycle, from data preparation and model development to deployment and monitoring. You will have the ...

Snap Engineering teams build fun and technically sophisticated products that reach hundreds of ... Experience working with machine learning, ranking infrastructures, and system design If you have a ...

Senior Machine Learning Engineer

Seattle, WA ยท On-site

$139K - $183K/yr

As a Machine Learning Engineer at Axon , you'll help build AI solutions that are transforming ... Architect and develop the infrastructure needed to train, evaluate, deploy, monitor, and ...

Proficient in JAVA & Python programming * Understanding of topic modelling, supervised & unsupervised machine learning * Plan the project milestones, resourcing and work distribution * Execute ...

Snap Engineering teams build fun and technically sophisticated products that reach hundreds of ... Experience working with machine learning, ranking infrastructures, and system design If you have a ...

Proficient in JAVA & Python programming * Understanding of topic modelling, supervised & unsupervised machine learning * Plan the project milestones, resourcing and work distribution * Execute ...

Showing results 41-60

Machine Learning Infrastructure Engineer information

See Seattle, WA salary details

$52.9K

$144.6K

$207.1K

How much do machine learning infrastructure engineer jobs pay per year?

As of Sep 14, 2026, the average yearly pay for machine learning infrastructure engineer in Seattle, WA is $144,605.00, according to ZipRecruiter salary data. Most workers in this role earn between $122,300.00 and $160,500.00 per year, depending on experience, location, and employer.

What is a machine learning infrastructure engineer?

A Machine Learning Infrastructure Engineer designs, builds, and maintains the systems that support the development and deployment of machine learning models. This includes managing data pipelines, optimizing model training and inference, and ensuring scalability and reliability in production environments. They work closely with data scientists, ML engineers, and DevOps teams to create efficient workflows and infrastructure. Key technologies often include cloud platforms, containerization, orchestration tools, and distributed computing frameworks.

What are the key skills and qualifications needed to thrive as a machine learning infrastructure engineer?

To thrive as a Machine Learning Infrastructure Engineer, you need a strong background in computer science, cloud computing, distributed systems, and experience with machine learning frameworks, often supported by a degree in a related field. Familiarity with tools such as Docker, Kubernetes, Terraform, as well as cloud platforms like AWS, GCP, or Azure, and certifications in cloud or DevOps technologies are highly valued. Strong problem-solving abilities, effective communication, and collaboration skills help engineers work seamlessly with data scientists and cross-functional teams. These skills are essential to design, implement, and maintain robust, scalable infrastructure that enables efficient machine learning development and deployment.

What are some common challenges faced by machine learning infrastructure engineers, and how can these be addressed on the job?

Machine Learning Infrastructure Engineers often face challenges such as ensuring infrastructure scalability, managing resource allocation, and maintaining system reliability while supporting rapid experimentation by data science teams. Balancing the needs for flexibility in research environments with production-grade stability requires a deep understanding of both engineering best practices and the unique requirements of machine learning workflows. Collaboration with data scientists, clear communication about infrastructure capabilities, and staying current with fast-evolving technologies are key strategies for success. Most companies encourage ongoing learning and provide opportunities to contribute to architecture decisions, which makes this a rewarding environment for problem-solvers and innovators.

What are popular job titles related to Machine Learning Infrastructure Engineer jobs in Seattle, WA?

For Machine Learning Infrastructure Engineer jobs in Seattle, WA, the most frequently searched job titles are:

What job categories do people searching Machine Learning Infrastructure Engineer jobs in Seattle, WA look for?

The top searched job categories for Machine Learning Infrastructure Engineer jobs in Seattle, WA are:

Infographic showing various Machine Learning Infrastructure Engineer job openings in Seattle, WA as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 75% Full Time, 20% Part Time, and 3% Contract. Highlights an 83% Physical, 2% Hybrid, and 15% Remote job distribution, with an average salary of $144,605 per year, or $69.5 per hour.

Machine Learning Engineer

Bellevue, WA โ€ข On-site

Other

Medical, Life, Retirement, PTO

Re-posted 4 days ago


Key responsibilities

  • Evaluate cutting-edge AI and ML technologies to identify solutions for Robinhood-specific problems.

  • Develop and implement scalable machine learning models, including ranking, recommendation systems, and reinforcement learning algorithms.

  • Design and conduct A/B tests to assess machine learning model performance and analyze experimental data to generate actionable insights.


Job description

Join us in building the future of finance.

Our mission is to democratize finance for all. An estimated $124 trillion of assets will be inherited by younger generations in the next two decades. The largest transfer of wealth in human history. If youโ€™re ready to be at the epicenter of this historic cultural and financial shift, keep reading.

About the team + role

We are building an elite team, applying frontier technologies to the worldโ€™s biggest financial problems. Weโ€™re looking for bold thinkers. Sharp problem-solvers. Builders who are wired to make an impact. Robinhood isnโ€™t a place for complacency, itโ€™s where ambitious people do the best work of their careers. Weโ€™re a high-performing, fast-moving team with ethics at the center of everything we do. Expectations are high, and so are the rewards. We're looking for an exceptional Machine Learning Engineer to help shape the future of our core platforms, products, and customer experiences. FinTech is one of the most complex and rapidly evolving spaces in technology, and the challenges we're tackling require deep innovation, critical thinking, and scale that don't always have strong precedents.

You'll take on a highly influential role shaping vision and execution across key strategic initiatives. You'll partner with cross-functional leaders, contribute to high-impact decisions, guide complex projects from concept to completion, and mentor others on the team. This is a role for someone who leverages modern tools and cuttingโ€‘edge methodologies as a core part of how they solve problems, and raises the bar for everyone around them.

This role is based in our Bellevue, WA, with in-person attendance expected at least three days per week.

At Robinhood, we believe in the power of in-person work to accelerate progress, spark innovation, and strengthen community. Our office experience is intentional, energizing, and designed to fully support high-performing teams.

What youโ€™ll do

As a Machine Learning Engineer on the AI Research and Development team, the primary focus will be on the implementation and evaluation of machine learning algorithms through rigorous experimentation and testing methodologies.

The responsibilities will include:

  • AI and ML Research: Evaluate cutting technologies, including but not limited to, transformer-based model architecture and large foundational models to identify solutions for Robinhood specific problems.
  • Model Development and Implementation: Develop and implement scalable machine learning models focusing on advanced ranking and recommendation systems, including expertise in Collaborative Filtering, Content Based Filtering, and Hybrid models, alongside proficiency in Learning to Rank (LTR) techniques for effective prioritization. Additionally, design reinforcement learning algorithms and apply multiโ€‘armed bandit strategies to optimize decisionโ€‘making in dynamic environments, balancing exploration and exploitation.
  • A/B Testing and Experimentation: Design and conduct A/B tests to assess the performance of different machine learning models. This includes setting up the test environment, monitoring performance, and analyzing results.
  • Data Analysis and Insight Generation: Analyze experimental data to extract actionable insights. Use statistical techniques to validate the findings and ensure their relevance and accuracy.
  • Crossโ€‘Functional Collaboration: Work closely with other engineering teams, data scientists, and the marketing team to integrate machine learning models into the product and ensure they meet business requirements. Present results to different stakeholders.
  • Tooling and Documentation: Build reusable libraries for common machine learning practices. Offer support and guidance to the usage of these tools. Maintain comprehensive documentation of libraries, models, experiments, and findings.
  • Telecommuting permitted.
What you bring
  • Bachelorโ€™s degree or foreign equivalent in Computer Science or related field and three years (3) of experience in job offered or related occupation.Alternatively, a Masters in Computer Science or related field and one year (1) of experience in job offered or related occupation
  • Education and/or experience must include:
    • Productionisation of ML models with focus on recommendations, ranking, or personalization;
    • Model development with classical ML techniques for tabular data;
    • Model development with modern ML techniques for sequential data;
    • Handsโ€‘on experience with architectural frameworks of large, distributed, and highโ€‘scale ML applications;
    • Produce robust business outcomes through comprehensive AB test and rigorous statistical analysis;
    • Proficiency in Python, SQL, XGBoost, Pytorch or Tensorflow to carry out production ready projects; and
    • Spark, Kafka, or Kubernetes.
  • Background checks required.
What we offer
  • Challenging, highโ€‘impact work to grow your career
  • Performance driven compensation with multipliers for outsized impact, bonus programs, equity ownership, and 401(k) matching
  • Best in class benefits to fuel your work, including 100% paid health insurance for employees with 90% coverage for dependents
  • Lifestyle wallet - a highly flexible benefits spending account for wellness, learning, and more
  • Employerโ€‘paid life & disability insurance, fertility benefits, and mental health benefits
  • Time off to recharge including company holidays, paid time off, sick time, parental leave, and more!
  • Exceptional office experience with catered meals, events, and comfortable workspaces.

In addition to the base pay range listed below, this role is also eligible for bonus opportunities + equity + benefits.

Base pay for the successful applicant will depend on a variety of jobโ€‘related factors, which may include education, training, experience, location, business needs, or market demands. The expected base pay range for this role is based on the location where the work will be performed and is aligned to the corresponding compensation zone.

Base Pay Range:

$161,138 - $200,000 per year

If our mission energizes you and youโ€™re ready to build the future of finance, we look forward to seeing your application.

Robinhood provides equal opportunity for all applicants, offers reasonable accommodations upon request, and complies with applicable equal employment and privacy laws. Inclusion is built into how we hire and workโ€”welcoming different backgrounds, perspectives, and experiences so everyone can do their best. Please review the Privacy Policy for your country of application.

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