Staff ML Engineer - AI Platform & Production

Qualtrics; Seattle (WA); On-site; USD 213,000 - 259,000; Full time

Benefits offered by this job

Wellness reimbursement

QGroup Communities

Hybrid work model

Job summary

Qualtrics is seeking an experienced Staff Machine Learning Engineer in Seattle to advance our ML/AI R&D strategy. You will design scalable architectures and collaborate across research, product, and engineering teams to deploy high-performance ML systems.

You will stay ahead of AI trends, contribute to platform development, and mentor junior engineers while helping close experience gaps across domains.

Qualifications

• Bachelor's or Master's degree in CS, AI, or related field.
• 7+ years of experience as ML Engineer or related role.
• Proficiency in Python, Java, or C++, with AI libraries (TensorFlow, PyTorch, Keras).
• Strong cloud experience (AWS, Azure, GCP) and deploying AI models.
• Excellent problem-solving and collaboration skills.
• Knowledge of LLMS deployment with DeepSpeed, Accelerate, FasterTransformer, Transformers-NeuronX a plus.

Responsibilities

• Design and develop robust ML architectures and AI frameworks for large-scale enterprise SaaS.
• Evaluate and select AI technologies and frameworks for performance and scalability.
• Collaborate across teams to guide ML strategy from research to production.
• Communicate clearly with researchers, product managers, and engineers; document architectures and decisions.
• Lead deployment of ML systems in production; optimize models for performance and cost.
• Provide technical guidance to ML platform teams; help build future ML platforms.
• Stay updated on AI advances and opportunities for their application.

Skills

Python

Java

C++

TensorFlow

PyTorch

Keras

Cloud computing

Education

Bachelor's or Master's degree in Computer Science, AI, or related field

Tools

DeepSpeed

Accelerate

FasterTransformer

Transformers-NeuronX

Job description

Qualtrics is seeking an experienced Staff Machine Learning Engineer in Seattle to advance our ML/AI R&D strategy. You will design scalable architectures and collaborate across research, product, and engineering teams to deploy high-performance ML systems.

You will stay ahead of AI trends, contribute to platform development, and mentor junior engineers while helping close experience gaps across domains.