Ground every answer in facts on this page and the original listing. We never invent Glassdoor-style reviews or salaries that are not in our data.
Website: dataideology.com
Public cache only — not an employee review.
Data Ideology seeks a Senior AI/ML Architect in the United States to lead architecture design for an edge AI assistant system on a contract basis. This discovery and architecture engagement produces validated AI architecture, technology assessments, and a proof-of-concept demonstrator. About This Position You'll drive architecture design for a bounded, edge-deployed AI system. This engagement focuses on selecting and configuring Small Language Models for edge deployment, designing domain restrictions and guardrails, and architecting retrieval-augmented inference pipelines. You'll produce implementable architecture documents and conduct feasibility assessments rather than training or deploying production models. Your Responsibilities Evaluate Small Language Model candidates for edge deployment against hardware constraints, latency requirements, domain restriction feasibility, and licensing; deliver technology assessments with trade-off analysis. Design domain restriction and guardrails architecture to constrain the SLM to defined scope and enforce retrieval-first behavior for safety-adjacent environments. Design the capability framework structuring how the system responds to operator queries, including scope isolation and incremental capability addition. Design the retrieval-augmented inference pipeline defining SLM context retrieval from local knowledge stores, retrieval strategies, and edge-optimized latency budgets. Evaluate cloud services for knowledge retrieval, model governance, and fleet-level model lifecycle management; recommend architectures aligned to enterprise standards. Define the ML lifecycle for model evaluation, adaptation through prompting and retrieval augmentation, versioning, and scaled distribution. Collaborate with Embedded Engineers and AWS Solutions Architects to ensure hardware feasibility and cloud architecture alignment. Document safety design principles, operational boundaries, and human-in-the-loop considerations as architecture artifacts for compliance and engineering review. Produce all architecture recommendations as Architecture Decision Records (ADRs) with explicit trade-off rationale. Requirements Bachelor's degree in Computer Science, Engineering, Mathematics, or equivalent professional experience. Demonstrated expertise designing AI/ML systems with Small Language Models, retrieval-augmented generation, and edge-optimized inference. Strong proficiency architecting constrained, bounded AI systems with safety-first design principles. Proven ability to evaluate AI/ML technologies against operational constraints (latency, memory, safety, licensing) and communicate trade-offs clearly. Experience with retrieval augmentation, knowledge store design, and context injection strategies. Hands-on familiarity with AWS AI/ML services (SageMaker, Bedrock, or equivalent) and cloud-based model governance. Excellent written communication; able to produce Architecture Decision Records engineers can build from.…
Generated for personal interview prep · 2026-07-14 UTC · getajob.ai