Job
Description
Key Responsibilities: Design, develop, and deploy machine learning models and AI solutions that address complex business challenges, particularly within the AEC domain. Build scalable, production-grade AI/ML pipelines, including data preprocessing, feature engineering, model training, validation, deployment, and monitoring. Collaborate with Data Engineers, Data Scientists, and other stakeholders to design and implement end-to-end AI/ML solutions. Ensure that deployed models are reliable, maintainable, and scalable while optimizing their performance in production environments. Develop APIs or microservices for integrating AI/ML models into business solutions. Optimize AI/ML workflows by implementing MLOps practices, including CI/CD pipelines, model retraining, and version control. Apply state-of-the-art algorithms and techniques such as deep learning, NLP, computer vision, and time-series analysis for domain-specific use cases. Maintain adherence to data privacy, security, and ethical AI standards throughout the lifecycle of AI/ML models. Stay abreast of the latest developments and advancements, including new and emerging technologies & best practices and new tools & software applications and how they could impact CDM Smith. Assist with the development of documentation, standards, best practices, and workflows for data technology hardware/software in use across the business. Performs other duties as required. Skills and Abilities: Strong expertise in building and deploying machine learning models using frameworks such as TensorFlow, PyTorch, or Scikit-learn. Hands-on experience with cloud-based AI/ML services, particularly in Microsoft Azure and Databricks. Proficiency in programming languages such as Python or R, with a strong understanding of libraries and tools for data science and machine learning. Experience with MLOps practices, including automated pipelines, model versioning, monitoring, and lifecycle management. Familiarity with distributed computing frameworks like Apache Spark and scalable AI/ML training techniques. Expertise in domain-specific AI techniques such as Natural Language Processing (NLP), computer vision, and predictive analytics. Knowledge of data privacy, security, and ethical AI principles, ensuring compliance with relevant standards. Excellent problem-solving and critical thinking skills to identify and address technical challenges effectively. Excellent interpersonal and presentation skills to build strategic relationships with colleagues, stakeholders, and partners. Strong critical thinking skills to generate innovative solutions and improve business processes. Ability to effectively communicate complex technical concepts to both technical and non- technical audiences. Detail oriented with the ability to assist with executing highly complex or specialized projects. Minimum Qualifications: Bachelors degree. 6 years of related experience. Equivalent additional related experience will be considered in lieu of a degree.
