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

Job Description

AI/ML Platform Architect

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

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Salary: $160,000 – $175,000

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

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

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

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

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

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

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

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competitors.

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The Opportunity

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

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

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

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

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optimized machine learning models in production.

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

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

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production.

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What You’ll Do

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

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establishing reusable patterns, architectural standards, and operational guardrails.

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

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

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architectures.

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

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expert on efficient deep learning infrastructure.

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

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and advanced deep learning capabilities for predictive telemetry analysis.

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

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

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

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automated recovery of production models.

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What You Bring

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

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

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

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

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deep learning or model optimization mechanisms.

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

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

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and container orchestration (ECS/EKS).

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

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deployment, automation, and continuous validation.

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

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

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What Is Offered

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 Competitive base salary of $156,000 – $175,000 per year.

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

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

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weeks total paid leave).

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 Complete medical, dental, and vision packages.

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

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