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Machine Learning Engineer

Seattle · Seattle, Washington, United States

Pay
Pay not listedSimilar roles state $165K–$240K
Work setting
Hybrid — work setting source
Description Location: Seattle, WA (Hybrid - 3 days/week in office) About ElastixAI:
Location type: Hybrid
From the employer’s posting
Employment
Full-time — employment source
Employment type: Full-time
From the employer’s posting
Team
Engineering — team source
Department: Engineering
From the employer’s posting

Before you apply

Sponsorship
Visa sponsorship not confirmed — sponsorship source
Do you now or will you in the future require visa sponsorship to work in the United States?
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Apply at ElastixAI

What you’ll work on

Full posting

We 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 qualifications

Core 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
  • 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 ElastixAI

We are building the next-gen AI inference platform.

In the employer’s words · Read in context · Company website ↗

Posting record

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Actively hiringFirst seen by us 11 days ago, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Oct 18, 2026 · 11 days ago
Recorded sightings
16
Last seen by us
Oct 29, 2026
Employer says posted
Feb 19, 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

View original posting ↗

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

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Pay

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Location & working pattern

Seattle, Washington, United States

Description Location: Seattle, WA (Hybrid - 3 days/week in office) About ElastixAI:
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