AI / ML Ops Platform Engineer- Onsite for Boulder Aerospace Company

AI/ML Platform Architect

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

Salary: $160,000 – $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 $156,000 – $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.