AI ML Architect

AI/ML Platform Architect

Location: Central Boulder, CO | Workplace: 100% Onsite

Salary: $150,000 – $175,000

Architect the future of intelligence in space—and define the core AI strategy and MLOps

infrastructure for a highly profitable, self-funded 40-person aerospace engineering firm

supporting mission-critical civil, commercial, and government space applications.

Our client is a highly specialized aerospace technology company that has built a reputation for

excellence in Space Domain Awareness (SDA) and live satellite operations. As they enter an

era of automated satellite operations, they are seeking an elite, hands-on technical leader to

design their enterprise AI footprint from the ground up, out-pacing legacy aerospace

competitors.

The Opportunity

As the AI/ML Platform Architect, you will sit at the crossroads of cutting-edge deep learning

innovation, infrastructure engineering, and real-time operational systems. This is a high-visibility,

foundational leadership role where you will establish engineering best practices for MLOps,

design end-to-end data ingestion pipelines, and build the compute frameworks required to run

optimized machine learning models in production.

You are stepping into a greenfield environment where the core software squads are eager to

deploy advanced analytics, predictive modeling, and intelligent agentic workflows into

production.

What You’ll Do

Lead the design, definition, and governance of the enterprise AI/ML platform,

establishing reusable patterns, architectural standards, and operational guardrails.

Architect and build end-to-end MLOps solutions, including data processing pipelines,

model training environments, and ultra-low-latency deployment and inference serving

architectures.

Deliver proofs-of-concept and platform modernization initiatives, serving as the resident

expert on efficient deep learning infrastructure.

Drive the exploration and development of intelligent automation, workflow integrations,

and advanced deep learning capabilities for predictive telemetry analysis.

Collaborate closely with cross-functional software, data engineering, and mission

operations teams to align AI initiatives with active satellite tracking systems.

Establish metrics, observability, and continuous delivery models for lifecycle tracking and

automated recovery of production models.

What You Bring

Academic Pedigree: Master’s degree or PhD in Computer Science, Mathematics,

Physics, Electrical Engineering, or a highly related technical discipline.

Deep Learning Depth: Strong hands-on proficiency with PyTorch, TensorFlow, or custom

CUDA-accelerated machine learning environments, with an understanding of efficient

deep learning or model optimization mechanisms.

Cloud Infrastructure Mastery: Minimum of 5 years of experience deploying scalable

distributed systems on AWS, with technical depth in networking, security best practices,

and container orchestration (ECS/EKS).

MLOps Core Focus: Demonstrated experience building pipelines for model registration,

deployment, automation, and continuous validation.

Clearance Eligibility: U.S. citizenship is required, along with the ability to obtain and

maintain a U.S. Government security clearance over time.

What Is Offered

Competitive base salary of $150,000 – $175,000 per year.

Predictable 40-hour standard work weeks with a stable, high-performing peer group.

Comprehensive benefits: 3 weeks of standard PTO plus 10 paid government holidays (5

weeks total paid leave).

Complete medical, dental, and vision packages.

401(k) retirement plan with a 3% company match.

Full relocation expense coverage with reasonable caps for out-of-state moves.