Enterprise AI Engineer — AI Solutions & NLP

Kidder Mathews; Seattle (WA); On-site; USD 130,000 - 170,000; Full time

Job summary

Kidder Mathews is seeking an Enterprise AI Engineer in Seattle to develop cutting-edge AI solutions and collaborate with cross-functional teams to implement them across business processes.

Responsibilities include designing ML architectures, preprocessing data, and applying NLP techniques, with a focus on accuracy, performance, and scalable deployment in cloud environments. A strong foundation in ML and real estate domain knowledge is valued.

Qualifications

• Bachelor's degree in computer science, data science, or a related field; a master's or Ph.D. is preferred.
• Experience developing and deploying AI solutions, preferably in a professional setting.
• Solid understanding of machine learning algorithms, deep learning frameworks, and statistical modeling.
• Proficiency in programming languages such as Python, R, or Java, and experience with AI libraries (e.g., TensorFlow, PyTorch).
• Strong analytical and problem-solving skills, with the ability to interpret complex data sets.
• Familiarity with cloud-based AI services and platforms (AWS, Azure, Google Cloud).

Responsibilities

• Develop and implement AI models and algorithms to solve complex business problems.
• Collaborate with stakeholders to identify AI project objectives, requirements, and success criteria.
• Collect, preprocess, and analyze large datasets to train and validate AI models.
• Design and optimize machine learning architectures, neural networks, and deep learning models.
• Utilize NLP techniques for text analysis and sentiment analysis.
• Collaborate with software engineers to integrate AI solutions into existing applications.

Skills

Python

TensorFlow

PyTorch

NLP

Data analysis

Education

Bachelor's degree in CS/DS

Master's/PhD preferred

Tools

AWS

Azure

Google Cloud

Job description

Kidder Mathews is seeking an Enterprise AI Engineer in Seattle to develop cutting-edge AI solutions and collaborate with cross-functional teams to implement them across business processes.

Responsibilities include designing ML architectures, preprocessing data, and applying NLP techniques, with a focus on accuracy, performance, and scalable deployment in cloud environments. A strong foundation in ML and real estate domain knowledge is valued.