Staff Engineer, Core ML (AI)

Location: Austin, TX, United States; hybrid

Company

hirify.global builds an AI execution layer for the physical economy, turning industrial expertise and technical documentation into production agent systems for manufacturers.

What you will do

• Develop algorithms that extract structured meaning from technical documents containing text, vector geometry, CAD, and raster content.
• Build document-understanding capabilities into tools powering long-running agentic systems.
• Improve agent planning, tool use, failure recovery, reliability, determinism, and effectiveness.
• Build training and evaluation pipelines for core models and agents, measuring changes against real customer data before release.
• Analyze production failures, dataset gaps, and bias; improve systems through data curation, labeling, synthetic data, algorithms, and model training.
• Track relevant research, bring promising techniques into production, and mentor engineers.

Requirements

• Hands-on AI/ML engineering experience with a track record of shipping ML-powered software and models to production.
• Experience training and fine-tuning production models, including the underlying datasets and pipelines.
• Experience operating ML evaluation pipelines with datasets, metrics, and regression testing for production models and agents.
• Experience profiling data distributions, identifying gaps and bias, and curating datasets for training and evaluation.
• Experience with vision and multimodal models, especially for technical PDFs or CAD containing text, vector geometry, and raster content.
• Strong knowledge of data structures, algorithms, software engineering principles, LLMs, deep learning systems, and applied ML.
• Experience debugging production ML systems with AI observability tools such as Langfuse or Opik and tracing failures to root cause.
• Proficiency in Python and relevant ML frameworks such as PyTorch and vLLM.
• Daily fluent use of AI coding tools, including writing effective prompts, iterating on incorrect output, and identifying code that works reliably.
• Strong technical decision-making, product judgment, communication, ownership, measurement rigor, and the ability to lead ambiguous problems through production delivery.
• Ability to review agent instructions, skills, and documentation for clarity, correctness, and reliability, and to raise the engineering bar through design reviews, code reviews, and mentoring.

Nice to have

• Expertise in agent harness design and execution, document extraction, structured data understanding, high-resolution computer vision, VLM fine-tuning and inference, retrieval systems, or agent evaluation and optimization.
• Computational geometry or experience with CAD and vector PDF formats.
• Go, used by the agent loop.
• Familiarity with construction, civil engineering, or related industries involving complex technical drawings and specifications.

Culture & Benefits

• Full-time role in a product engineering team working on production systems rather than research publications or isolated customer projects.
• Competitive compensation, meaningful equity, and employer-paid benefits.
• Flexible PTO and access to the latest AI tools.
• Values-driven environment emphasizing ownership, curiosity, velocity, low ego, and customer outcomes.