POSITION PROFILE

Company Profile

DigitalXNode helps businesses accelerate digital transformation through IT staffing, AI solutions, software development, and digital marketing services. The company focuses on connecting organizations with top technology talent while delivering innovative, scalable, and business-driven solutions.

Roles & Responsibilities

• Design, build, and deploy end-to-end ML pipelines.
• Develop NLP/LLM, Computer Vision, Graph Neural Network, and Time-Series forecasting models.
• Build scalable MLOps infrastructure and production ML systems.
• Lead ML strategy, architecture, and technical decisions.
• Mentor ML engineers and establish engineering standards.
• Integrate ML models with Revit, Procore, and Autodesk Construction Cloud.
• Collaborate with cross-functional teams and AEC domain experts.
• Drive responsible AI practices and production model monitoring.

Experience

5–8 years of hands-on Machine Learning experience with at least 2 years in a Technical Lead or Senior Individual Contributor role.

Education

Bachelor’s or Master’s Degree in Computer Science, Artificial Intelligence, Machine Learning, Statistics, Computational Engineering, or a related field (or equivalent practical experience).

Technical Skills

PyTorch, Python, NumPy, SciPy, Pandas, Scikit-learn, AWS SageMaker, Vertex AI, Azure ML, MLflow, Weights & Biases, Docker, Kubernetes, ECS, Pinecone, Weaviate, Turbopuffer, Feature Stores, Vector Databases, CI/CD, API Development, Cloud ML Infrastructure.

Programmatic Skills

Python, Deep Learning, Machine Learning, NLP, LLMs, Computer Vision, Graph Neural Networks, Time-Series Forecasting, Scientific Computing, REST APIs, Containerization, Cloud Deployment.

AI Experience

Deep Learning, NLP, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Prompt Engineering, Embedding Models, Computer Vision, Graph Neural Networks (GNNs), Reinforcement Learning, Generative AI, Transformers, Diffusion Models, Time-Series Forecasting, Physics-Informed Models, AI Model Deployment & Monitoring.

Managerial Experience

Lead the Machine Learning function, mentor engineers, define engineering standards, drive ML strategy, collaborate with CTO and Principal Engineer, lead research initiatives.

Operational Experience

Production ML deployment, MLOps, automated retraining pipelines, model monitoring, feature stores, embedding infrastructure, vector search, data pipelines, experiment tracking, A/B testing, production analytics.

Client-Centric Experience

Collaborate with architects, engineers, project managers, estimators, owners, contractors, and AEC stakeholders to solve real-world construction challenges using AI.