Senior Machine Learning Engineer - RAI
Redmond, WA, US
- Pay
- Pay not listedSimilar roles state $165K–$240K
- Work setting
- Not stated
- Employment
Full-time — employment source
Employment type in the employer’s posting: FULL_TIME
From the employer’s posting
What you’ll work on
Full postingDesign and build production systems for ML training, evaluation, and inference
Turn ML models and research advances into reliable, scalable product capabilities
Own complex engineering projects from design through production deployment
Build shared infrastructure, services, and reusable components for multiple models
Diagnose and resolve performance, scalability, and reliability problems
From the employer’s posting
Design and build production systems for machine learning training, evaluation, inference, and operation.
Transform machine learning models and research innovations into reliable, scalable product capabilities.
Own complex engineering projects from technical design through implementation and production deployment.
Develop infrastructure, services, and reusable components that support multiple models and workloads.
Diagnose and resolve challenges involving system performance, scalability, reliability, and efficiency.
Tools in this posting
- C
- C#
- C++
- Java
- JavaScript
- Python
Source — Tool mentions in context
Design and build production systems for machine learning training, evaluation, inference, and operation. Transform machine learning models and research innovations into reliable, scalable product capabilities. Own complex engineering projects from technical design through implementation and production deployment. Develop infrastructure, services, and reusable components that support multiple models and workloads. Diagnose and resolve challenges involving system performance, scalability, reliability, and efficiency. Partner with applied scientists and software engineers to integrate modeling advances into production systems. Contribute to architectural decisions and coordinate technical work across components and partner teams. Incorporate security, privacy, safety, and Responsible AI considerations throughout system design and development. Mentor other engineers and contribute to strong engineering practices across the team. Bachelor's Degree in Computer Science or related technical field AND 4+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience. These requirements include but are not limited to the following specialized security screenings: Master's or Doctorate degree in Computer Science or a related technical field, with a focus on machine learning or related areas, AND 5+ years of technical engineering experience, or equivalent experience. Experience building machine learning infrastructure or platforms that support multiple models or workloads. Experience contributing to architecture and delivering technical initiatives involving multiple components or teams. Experience with distributed systems and large-scale machine learning workloads. Demonstrated interest in AI safety and Responsible AI, including building systems that support the safe and responsible development or deployment of AI capabilities. Demonstrated experience deploying and scaling machine learning models or pipelines in production. Software engineering, system design, and problem-solving skills. Experience building systems for one or more stages of the machine learning lifecycle, such as data processing, training, evaluation, or inference. Ability to independently deliver complex technical projects and collaborate effectively across science and engineering disciplines.
Posting record
Report an errorActively hiringFirst seen by us 9 days ago, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Oct 20, 2026 · 9 days ago
- Recorded sightings
- 65
- Last seen by us
- Oct 29, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
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Job description
Design and build production systems for machine learning training, evaluation, inference, and operation. Transform machine learning models and research innovations into reliable, scalable product capabilities. Own complex engineering projects from technical design through implementation and production deployment. Develop infrastructure, services, and reusable components that support multiple models and workloads. Diagnose and resolve challenges involving system performance, scalability, reliability, and efficiency. Partner with applied scientists and software engineers to integrate modeling advances into production systems. Contribute to architectural decisions and coordinate technical work across components and partner teams. Incorporate security, privacy, safety, and Responsible AI considerations throughout system design and development. Mentor other engineers and contribute to strong engineering practices across the team. Bachelor's Degree in Computer Science or related technical field AND 4+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience. These requirements include but are not limited to the following specialized security screenings: Master's or Doctorate degree in Computer Science or a related technical field, with a focus on machine learning or related areas, AND 5+ years of technical engineering experience, or equivalent experience. Experience building machine learning infrastructure or platforms that support multiple models or workloads. Experience contributing to architecture and delivering technical initiatives involving multiple components or teams. Experience with distributed systems and large-scale machine learning workloads. Demonstrated interest in AI safety and Responsible AI, including building systems that support the safe and responsible development or deployment of AI capabilities. Demonstrated experience deploying and scaling machine learning models or pipelines in production. Software engineering, system design, and problem-solving skills. Experience building systems for one or more stages of the machine learning lifecycle, such as data processing, training, evaluation, or inference. Ability to independently deliver complex technical projects and collaborate effectively across science and engineering disciplines.
Source details
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- Pay
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- Location & working pattern
Redmond, WA, US
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