Machine Learning Engineer
Seattle, Washington, United States
- Pay
- Pay not listed
- Work setting
Hybrid stated — work setting source
Description Location: Seattle, WA (Hybrid - 3 days/week in office) About ElastixAI:
Read the full posting- Employment
Full-time — employment source
Employment type in the employer’s listing: FullTime
From the employer’s posting
What you’ll work on
Full postingWe are looking for a talented Machine Learning Engineer to play a key role in building our core AI inference platform.
Design, develop and maintain core components of the ML platform
Research, prototype and implement ML techniques to optimize inference performance
Work with systems and cloud engineers on efficient hardware utilization
Contribute to the design of APIs and tools for inference solutions
From the employer’s posting
We are looking for a talented Machine Learning Engineer to play a key role in building our core AI inference platform. You will be responsible for designing and developing critical components, including ML model deployment, innovative model optimization pipelines, and performance benchmarking and simulation workflows. This is a highly interdisciplinary role where you'll collaborate closely with our multi-disciplinary team to ensure our entire stack works in harmony to deliver optimal AI inference solutions.
Design, develop, and maintain core components of our ML platform
Research, prototype, and implement advanced ML techniques to optimize inference performance across diverse hardware targets.
Collaborate with systems and cloud engineers to ensure efficient utilization of underlying hardware resources.
Contribute to the design of APIs and tools that enable seamless integration and management of our inference solutions.
What you’ll bring
All qualificationsCore experience
- 3+ years of machine learning R&D and deployment experience
- PhD or MS in Computer Science, Computer Engineering, or a related field
- Strong proficiency in Python or C++
- Proficiency in at least one ML framework such as PyTorch, TensorFlow, or JAX
- Solid software engineering practices: data structures, algorithms, and testing
Qualification wording
3+ years of machine learning R&D and deployment experience.
PhD/MS in Computer Science, Computer Engineering, or a related field.
Strong proficiency in one or more programming languages such as Python, or C++.
Proficiency in at least one ML framework (e.g., PyTorch, TensorFlow, JAX).
Solid understanding of software engineering best practices, including data structures, algorithms, and testing.
Education & alternatives
Required Qualifications: - PhD/MS in Computer Science, Computer Engineering, or a related field. - 3+ years of machine learning R&D and deployment experience.
Tools in this posting
- C++
- Python
- AWS
- Azure
- Docker
- Google Cloud (GCP)
- Kubernetes
- PyTorch
- TensorFlow
Source — Tool mentions in context
- 3+ years of machine learning R&D and deployment experience. - Strong proficiency in one or more programming languages such as Python, or C++. - Proficiency in at least one ML framework (e.g., PyTorch, TensorFlow, JAX).
- Familiarity with performance analysis, profiling, and optimization techniques. - Experience with cloud platforms (AWS, GCP, Azure). - Experience with containerization and orchestration technologies (e.g., Docker, Kubernetes).
- Experience with cloud platforms (AWS, GCP, Azure). - Experience with containerization and orchestration technologies (e.g., Docker, Kubernetes). What We Offer:
- Strong proficiency in one or more programming languages such as Python, or C++. - Proficiency in at least one ML framework (e.g., PyTorch, TensorFlow, JAX). - Solid understanding of software engineering best practices, including data structures, algorithms, and testing.
Benefits in the posting
Full benefits wording- Competitive compensation and startup equity package
- Comprehensive medical, dental, and vision coverage (100% paid by employer)
- Paid parental leave
- Gym or fitness benefit
- Commuter benefit
- Investment in employee learning & development
From the employer’s posting.
About elastix
We are building the next-gen AI inference platform.
In the employer’s words · Read in context
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Oct 18, 2026 · today
- Recorded sightings
- 2
- Employer says posted
- Feb 19, 2026
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
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- Check the listed location, eligibility and core experience before starting.
- Ask the employer about the pay range before committing time to the process.
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Job description
About Elastix AI
We are building the next-gen AI inference platform.
Description
Location: Seattle, WA (Hybrid - 3 days/week in office)
About ElastixAI:
ElastixAI is an early-stage startup poised to revolutionize AI inference infrastructure. We are developing a cutting-edge AI inference solution that dramatically improves efficiency. Our solution is going to dynamically adapt to any deployment, constantly evolving to power the next generation AI use cases.
Role Summary:
We are looking for a talented Machine Learning Engineer to play a key role in building our core AI inference platform. You will be responsible for designing and developing critical components, including ML model deployment, innovative model optimization pipelines, and performance benchmarking and simulation workflows. This is a highly interdisciplinary role where you'll collaborate closely with our multi-disciplinary team to ensure our entire stack works in harmony to deliver optimal AI inference solutions.
Key Responsibilities:
Design, develop, and maintain core components of our ML platform, focusing on scalability, reliability, and ease of use.
Research, prototype, and implement advanced ML techniques to optimize inference performance across diverse hardware targets.
Collaborate with systems and cloud engineers to ensure efficient utilization of underlying hardware resources.
Contribute to the design of APIs and tools that enable seamless integration and management of our inference solutions.
Required Qualifications:
PhD/MS in Computer Science, Computer Engineering, or a related field.
3+ years of machine learning R&D and deployment experience.
Strong proficiency in one or more programming languages such as Python, or C++.
Proficiency in at least one ML framework (e.g., PyTorch, TensorFlow, JAX).
Solid understanding of software engineering best practices, including data structures, algorithms, and testing.
Excellent problem-solving abilities and a knack for tackling complex technical challenges.
Strong communication skills and a proven ability to collaborate effectively in a cross-functional team environment.
Ability to thrive in a fast-paced, dynamic startup environment.
Preferred/Bonus Qualifications:
Experience with training generative machine learning models.
Experience with optimizing the performance of machine learning models.
Experience leading research initiatives in Machine Learning, Natural Language Processing, and related fields.
Familiarity with performance analysis, profiling, and optimization techniques.
Experience with cloud platforms (AWS, GCP, Azure).
Experience with containerization and orchestration technologies (e.g., Docker, Kubernetes).
What We Offer:
A chance to be a foundational engineer in an innovative AI startup.
A dynamic and collaborative work environment and the change to have a significant impact on new technology
The opportunity to work on challenging problems at the intersection of ML, software, and systems.
Competitive compensation and startup equity package
Comprehensive medical, dental, and vision coverage (100% paid by employer)
Flexible Time Off (FTO)
Paid parental leave
Gym or fitness benefit
Commuter benefit
Investment in employee learning & development
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
Seattle, Washington, United States
Description Location: Seattle, WA (Hybrid - 3 days/week in office) About ElastixAI:
- Work authorization
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