Software Engineer I, Machine Learning

• Design, develop, and maintain software systems and applications based on user or system design specifications.
• Write clean, well-documented, testable code across the full stack (Python, TypeScript/JavaScript, or other languages as required).
• Build, train, evaluate, and iterate on machine-learning pipelines, including data preprocessing, model selection, fine-tuning, and performance benchmarking.
• Create and update technical specifications, architecture diagrams, and user-facing documentation.
• Develop and execute unit, integration, and regression tests; participate in code review.
• Analyze existing systems and programs to identify opportunities for performance improvements and bug fixes.
• Prototype new features rapidly in response to product requirements and user feedback.
• Collaborate cross-functionally with product, design, and data teams to translate requirements into technical solutions.
• Participate in agile ceremonies (sprint planning, standups, retrospectives) and contribute to sprint deliverables.
• Adhere to security best practices and contribute to compliance efforts as directed.

Focus Area: Machine Learning

• Design and implement ML pipelines end-to-end: data ingestion, feature engineering, model training, evaluation, and deployment.
• Evaluate pre-trained models and fine-tune large language models (LLMs) or vision models for AEC document understanding tasks.
• Monitor deployed model performance, detect drift, and implement retraining workflows.
• Research emerging ML techniques and recommend adoption where appropriate.
• Maintain experiment tracking and reproducibility standards (e.g., MLflow, Weights & Biases).

• Bachelor’s degree in Computer Science, Software Engineering, or a closely related field, OR equivalent practical experience.
• Demonstrated proficiency in at least one modern programming language (Python, TypeScript, JavaScript, Go, or similar).
• Foundational understanding of software design principles, data structures, and algorithms.
• Familiarity with version control (Git) and collaborative development workflows (pull requests, code review).
• Ability to read, write, and communicate technical concepts clearly in English.
• Ability to work independently in a remote environment with minimal supervision., * Experience with machine-learning frameworks (PyTorch, TensorFlow, scikit-learn, Hugging Face Transformers).
• Exposure to cloud infrastructure (AWS, Azure, or GCP) and containerization (Docker, Kubernetes).
• Experience with document processing, OCR, or computer vision tasks.
• Familiarity with REST API design, GraphQL, or similar service-oriented architectures.
• Prior internship, co-op, or project experience in a software engineering context.