Space AI/ML Platform Architect — Onsite Boulder

Technical Integrity, LLC; Boulder (CO); On-site; USD 150,000 - 175,000; Full time

Benefits offered by this job

Relocation assistance

Comprehensive benefits

PTO & holidays

Medical/Dental/Vision

401(k) match

Relocation expense coverage

Job summary

Technical Integrity, LLC seeks an AI/ML Platform Architect to design an enterprise AI footprint for space-focused applications from a greenfield baseline. You will govern platform decisions, build end-to-end MLOps, and enable real-time inference alongside mission-critical data pipelines.

You will partner with software, data engineering, and operations teams to deploy scalable, low-latency ML systems in AWS, mentoring engineers and driving standards, observability, and secure, compliant AI

Qualifications

• Advanced technical degree with ML/platform focus and strong research background.
• Hands-on experience designing scalable ML platforms and MLOps pipelines.
• Experience deploying distributed systems in cloud environments (AWS).
• Ability to define governance and security for AI/ML workloads.

Responsibilities

• Lead design and governance of the enterprise AI/ML platform.
• Architect end-to-end MLOps pipelines and deployment tooling.
• Build low-latency inference serving and training environments.
• Deliver proofs-of-concept and platform modernization initiatives.
• Collaborate with software, data engineering, and mission operations teams.
• Define metrics, observability, and continuous delivery for models.

Skills

PyTorch

TensorFlow

CUDA

AWS

MLOps

Distributed systems

Education

Master's degree in CS/Math/Physics/EE

PhD in a related field

Tools

ECS/EKS

Container orchestration

Job description

Technical Integrity, LLC seeks an AI/ML Platform Architect to design an enterprise AI footprint for space-focused applications from a greenfield baseline. You will govern platform decisions, build end-to-end MLOps, and enable real-time inference alongside mission-critical data pipelines.

You will partner with software, data engineering, and operations teams to deploy scalable, low-latency ML systems in AWS, mentoring engineers and driving standards, observability, and secure, compliant AI