Software Engineering Intern- AI/ML Backend (Spring 2026)

Descrição da Vaga

Requisitos

• You recently completed a degree in Computer Science, Machine Learning, Data Science, or a related field (or have equivalent practical experience) and are looking for a runway to transition into a full-time role
• You have a strong foundation in Python and are comfortable writing production-quality code, not just notebook prototypes
• You have coursework or project experience in machine learning and understand the fundamentals of training, evaluation, and iteration
• You are comfortable working with data — cleaning it, analyzing it, visualizing it, and drawing conclusions from it
• You are a highly collaborative, self-motivated communicator who thrives in ambiguity, takes ownership of your work without waiting for instructions, and isn't afraid to say "I don't know yet" while moving fast
• You are comfortable participating in virtual meetings and in-person collaboration at our Vancouver, WA HQ
• Experience building APIs with FastAPI, Flask, or similar Python web frameworks and deploying models behind them
• Familiarity with HuggingFace Transformers and the model hub ecosystem
• Experience training models from scratch or fine-tuning using supervised fine-tuning or parameter-efficient fine-tuning techniques
• Contributions to open-source projects or published research
• Startup experience: proven ability to move fast on a small engineering team
• Experience or interest in the home building, home remodeling, construction, or real estate industries

Responsabilidades

• We expect you to hit the ground running and ship real production code from day one
• You will act as a core member of our R&D team, working alongside our Head of R&D and the broader engineering team to build the services and infrastructure that turn ML model outputs into user-facing value — focusing on backend integration, evaluation, and production readiness rather than model research
• Build and maintain FastAPI services in Python that serve ML models and integrate into our broader microservices architecture
• Build evaluation frameworks and benchmarks to systematically measure quality across our ML services
• Work with geometric and spatial data using libraries like Shapely, NumPy, and OpenCV to process, validate, and post-process model outputs into production-ready formats
• Improve and extend our vision and language pipelines for construction document understanding, including tasks such as instance segmentation, classification, and geometric shape analysis
• Integrate ML outputs into production workflows orchestrated by our Restate durable execution engine
• Adopt and help shape our agentic coding practices — our team embraces tools like Cursor, Copilot, and Claude Code to accelerate development
• Work with vector embeddings and semantic search infrastructure using pgvector
• Contribute to our TypeScript backend and React frontend as features require end-to-end implementation
• Run data analysis and experimentation to identify model failure modes and drive improvements with measurable results
• Contribute to our human-in-the-loop annotation workflows, helping design pre-annotation pipelines and process crowdsourced labeling results