AI/ML Platform Architect

SpaceNav; Boulder (CO); On-site; USD 150,000 - 175,000; Full time

Job summary

SpaceNav is seeking an experienced AI/ML Platform Architect to lead their AI-centric strategy and roadmap in Boulder, Colorado. The ideal candidate will drive the development of AI initiatives, working hands-on with infrastructure and MLOps best practices. Responsibilities include designing and implementing end-to-end AI solutions, as well as collaborating with cross-functional teams to align AI projects with company goals. The salary range for this position is $150,000 - $175,000 per year.

Qualifications

• Strong hands-on experience with AWS services, including IAM, VPC, S3, and Lambda.
• Minimum of 5 years experience in AI/ML engineering or related fields.
• Proven experience designing and building AI systems, including LLMs.

Responsibilities

• Lead proofs of concept and modernization initiatives providing technical leadership.
• Design and govern the enterprise AI/ML platform and operational standards.
• Architect and implement AI/ML solutions including data processing pipelines.

Skills

AWS cloud services

MLOps practices

Distributed systems

Scalable platform architecture

Model deployment

AI/ML engineering

Education

Master’s degree in Computer Science, Mathematics, Physics, Engineering, or related field

Job description

Job Description: SpaceNav is looking for an experienced AI/ML Platform Architect to help drive the company’s AI-centric strategy and roadmap. The ideal candidate is a self-motivated, collaborate leader who will play a critical role in developing and executing key AI initiatives.

As an AI/ML Platform Architect, you will leverage your expertise in machine learning infrastructure, cloud-native technologies, data platforms, and scalable system design to build and maintain the foundation for next-generation AI capabilities across SpaceNav. You will play a key role in architecting and operationalizing AI/ML workflows, enabling reliable model development, deployment, monitoring, and lifecycle management in support of mission-critical aerospace applications. In addition to designing robust and scalable AI platforms, you will help define engineering best practices for MLOps, automation, and cloud infrastructure, while collaborating closely with software, data, and mission operations teams. This is a hands‑on leadership role ideal for an engineer who thrives at the intersection of AI innovation, platform engineering, and operational excellence, where scalability, reliability, and performance are essential.

Responsibilities

• Lead and deliver proofs of concept, platform migrations, and modernization initiatives while providing technical leadership and strategic guidance across engineering teams.
• Design, define, and govern the enterprise AI/ML platform, including architectural standards, reusable patterns, best practices, and operational guardrails adopted across all delivery teams.
• Architect and implement end‑to‑end AI/ML solutions, including data ingestion and processing pipelines, model training and deployment workflows, and scalable inference and serving architectures.
• Drive the development of new AI‑enabled products, intelligent automation capabilities, and advanced analytics use cases that support SpaceNav’s strategic objectives.
• Collaborate cross‑functionally with software engineering, operations, and business stakeholders to align AI initiatives with mission and product goals.
• Establish and promote MLOps best practices for model lifecycle management, monitoring, scalability, reliability, and continuous delivery.

Qualifications

• Master’s degree in Computer Science, Mathematics, Physics, Engineering, or a related technical field.
• Strong hands‑on experience with AWS cloud services and infrastructure, including IAM, VPC, S3, Lambda, ECS/EKS, Step Functions, CloudWatch, and cloud networking and security best practices.
• Minimum of 5 years of experience in AI/ML engineering, platform engineering, software engineering, or related technical disciplines.
• Proven experience designing, building, and operating AI/ML systems, including large language models (LLMs) and/or classical machine learning solutions, along with the supporting infrastructure and deployment environments.
• Experience with MLOps practices and tools for model deployment, monitoring, automation, and lifecycle management.
• Strong understanding of distributed systems, scalable platform architecture, and cloud-native application design.
• Ability to obtain and maintain a U.S. Government security clearance.

The salary range for this role is $150,000 - $175,000 per year.