Staff Engineer, Applied ML

Location: Austin, TX, United States; hybrid

Company

hirify.global builds an AI execution layer for the physical economy, turning industrial expertise and technical customer data into production agents for manufacturing workflows.

What you will do

• Work directly with Forward Deployed Engineers and design customers to build end-to-end solutions for complex industrial workflows.
• Turn customer-specific solutions into reusable capabilities that can be deployed across customers.
• Improve models, agent harnesses, retrieval systems, evaluation methodologies, and production ML pipelines.
• Debug production systems, including edge cases and failure modes in ML pipelines and retrieval systems.
• Build evaluation systems with datasets, scoring approaches, and repeatable regression testing.
• Collaborate with Product Engineering, FDEs, Core ML engineers, and design partners.

Requirements

• Strong software engineering background with experience owning and shipping production systems end to end.
• Deep experience with data structures and data modeling across relational and graph databases, including schema design, normalization, and indexing strategy.
• Hands-on experience with LLMs, RAG systems, and agent harnesses, including how they work, fail, and should be evaluated.
• Experience with retrieval systems, model training and fine-tuning, evaluation design and dataset curation, or debugging production ML systems.
• Experience working directly with customers or field teams and turning customer needs into product capabilities.
• Experience generalizing a solution built for one customer so other customers can deploy it.
• Experience building and maintaining features across a multi-service architecture, with strong proficiency in languages such as Python and Go.
• Daily, fluent use of AI coding tools, including writing effective prompts and critically reviewing generated code.
• Ownership mindset, product judgment, systems thinking, clear communication, and a bias toward shipping reliable production systems.

Nice to have

• Vision and multimodal models for technical documents such as PDFs and CAD files containing text, vector geometry, and raster content.
• Construction, civil engineering, or other industrial-domain experience.
• Open-source models such as Qwen or DeepSeek and serving systems such as vLLM or KServe.
• Hands-on PyTorch or similar experience for model training and fine-tuning.

Culture & Benefits

• Full-time role with competitive compensation, meaningful equity, and employer-paid benefits.
• Flexible PTO and access to the latest AI tools.
• Values-driven culture focused on ownership, curiosity, velocity, and team outcomes.
• Work with manufacturing and AI leaders on a category-defining industrial platform.