AI Training Infrastructure Engineer

Opedia Technologies

Role involves building distributed systems for AI model training at a growing AI infrastructure company. Collaborate closely with engineering teams to solve complex challenges.

Posted 7/21/2026full-timeBellevue • Washington • 🇺🇸 United StatesMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and scaling distributed training infrastructure for large AI models, with a strong focus on reliability, efficiency, and resource utilization. Proficient in integrating AI models into production pipelines and improving developer experience through automation and best practices.

Highest-signal resume keywords

Distributed Training SystemsLarge-Scale Machine Learning InfrastructureMulti-Node GPU TrainingProduction Machine Learning PipelinesProgramming Skills

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Distributed Training InfrastructureLarge AI ModelsFault ToleranceCheckpointingRecovery SolutionsTraining OperationsSystem ReliabilityScalability ChallengesEfficiency ImprovementComplex Distributed Systems

Soft Skills

OwnershipProblem-SolvingIndependence

Tools & Technologies

Automation ToolsAI Infrastructure PlatformPerformance Engineering

Industry Keywords

AI ModelsMachine LearningTraining PipelinesOperational Processes

Tech Stack

Tools & technologies

Distributed SystemsNode.js

About the role

Key responsibilities & impact

Build and scale distributed training infrastructure supporting large AI models across large GPU clusters.
Design and improve systems that increase training reliability, efficiency, and resource utilization.
Develop solutions for fault tolerance, checkpointing, recovery, and large-scale training operations.
Integrate AI models into production training pipelines in partnership with platform, orchestration, and performance engineering teams.
Diagnose and resolve issues impacting training throughput, stability, reliability, and cost efficiency.
Build tools and automation that improve the developer experience for AI researchers and engineers.
Establish best practices for training infrastructure, operational processes, and platform reliability.
Contribute to the evolution of the AI infrastructure platform as an early member of the engineering team.

Requirements

What you’ll need

Hands-on experience building and operating distributed training systems or large-scale machine learning infrastructure.
Experience supporting large AI models, foundation models, post-training workflows, or similar ML systems.
Strong understanding of the reliability, scalability, and efficiency challenges associated with multi-node GPU training.
Experience integrating training systems with production machine learning pipelines.
Strong programming skills and experience working with complex distributed systems.
Ability to independently own technically challenging projects in a fast-moving engineering environment.
Comfortable operating with high ownership and limited process overhead.

Benefits

Comp & perks

Competitive base pay for Bellevue market
Certain roles are eligible for additional rewards, including merit increases, annual bonus, and stock. These awards are allocated based on individual performance
U.S. based employees have access to medical, dental, and vision insurance
401(k) plan and company match
Paid holidays.