Principal AI Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Collaborate with a team of technologists to develop foundation models and generative AI tools.

• Create and implement agentic workflows — multi-agent orchestration (e.g., CrewAI, LangGraph, AutoGen), tool utilization, multi-step planning, and human-in-the-loop checkpoints — to streamline complex engineering processes.

• Set up evaluation metrics, guardrails, and failure-mode assessments for agent systems to guarantee safety, reliability, and readiness for production.

• Construct scalable data pipelines to handle a variety of data sources utilized in production ML systems, including BIM, CAD, and infrastructure design data.

• Engage with extensive, multi-modal datasets — incorporating text and geometric data — to innovate preprocessing, augmentation, analysis, and content comprehension techniques.

• Convert unstructured infrastructure and design data into formats suitable for machine learning applications.

• Spearhead collaboration across functions with ML Research Scientists and Engineers to ensure data formats align with downstream training and fine-tuning of LLMs.

• Implement deduplication, normalization, and validation strategies to guarantee high-quality data in production settings.

• Design and enhance pipelines for scalability, reproducibility, and cloud-based deployment.

• Guide junior engineers and offer technical direction on challenging data issues.

• Propel technical decision-making and shape best practices within the team.

• Conduct requirements analysis with senior stakeholders, ensuring that technical solutions align with both immediate project requirements and long-term research goals.

• Present findings and technical insights through quantitative analysis, visual representations, and thorough documentation.

• Engage in agile workflows, ensuring adaptability and responsiveness to changing project demands.

• Take part in technical planning and the development of project roadmaps.

⛳️ Requirements

• A Master's or PhD in Computer Science, Engineering, or a related discipline is required.

• 5–8+ years of experience in Engineering, Machine Learning, or associated fields.

• Extensive programming and software engineering expertise, robust computer science fundamentals (data structures, algorithms, system design), and a proven history of delivering and maintaining production-grade code rather than merely prototypes or notebooks.

• Demonstrated technical leadership in intricate projects and steering technical direction across cross-functional teams.

• Strong background in geometric data modeling and processing, including intricate 2D/3D representations, computational geometry, and data architectures.

• Familiarity with machine learning principles and frameworks, as well as understanding how data is structured for training.

• Capability to translate research concepts into production-ready systems.

• Exceptional communication skills, with the ability to influence and guide technical decisions.

🏝️ Benefits

• Comprehensive and competitive health benefits plan

• Matching 401k contributions

• 20 days annual PTO

• Primarily remote work with occasional annual team onsites.