Senior Applied ML Engineer

Role overview

Responsibilities

• check_circle Develop and optimize CNN and LLM-powered models for computer vision, document extraction, and automated construction workflows.
• check_circle Prototype, fine-tune, and assess models for NLP tasks such as classification, entity recognition, and summarization of construction data.
• check_circle Build scalable ML pipelines and backend services that integrate into production-grade agents and digital platforms.
• check_circle Drive the end-to-end ML lifecycle: from experimentation and training, to deployment, monitoring, and continuous improvement.
• check_circle Integrate retrieval, ML, and rules-based methods to deliver reliable, explainable, and supportable features.
• check_circle Collaborate closely with product managers, software engineers, and construction domain experts to solve real-world challenges with measurable business impact.

Basic qualifications

• Bachelor’s or Master’s degree in Computer Science, Machine Learning, or related field.
• 5+ years of experience designing and deploying applied ML systems at scale.
• Experience with computer vision (CNNs, object detection, segmentation) and natural language processing (LLMs, embeddings, transformers).
• Strong proficiency in Python and ML frameworks (PyTorch, TensorFlow, Hugging Face).
• Experience with ML Ops platforms and deploying ML systems into production (MLflow, Kubeflow or equivalent).
• Experience with APIs, CI/CD pipelines, cloud platforms (AWS/Azure/GCP).
• Ability to clearly communicate technical concepts to both engineers and non-technical stakeholders.

Preferred qualifications

• Experience applying ML in construction, CAD/BIM, architecture, or digital twin platforms is preferred.
• Familiarity with graph-based retrieval, RAG pipelines, or multimodal ML is preferred.