Join us as an AI/MS Engineer, where we’re pioneering innovative solutions to maximize space utilization. Our mission is to empower real estate owners with cutting-edge technology, transforming traditional building infrastructure into responsive, data-driven environments. We create digital twins of spaces, providing facility managers with user-friendly automation and operational efficiency. Be part of a team shaping the future of space optimization through AI and Machine Learning.
– Data Preprocessing: Collect, clean, and preprocess large datasets for training and evaluation of machine learning models.
– Model Development: Design and develop machine learning algorithms and models that are scalable, efficient, and accurate.
– Feature Engineering: Identify and engineer relevant features from raw data to enhance model performance.
– Model Training: Train and fine-tune machine learning models using appropriate techniques, frameworks, and libraries.
– Evaluation: Evaluate the performance of models using relevant metrics and implement improvements as needed.
– Deployment: Deploy machine learning models into production environments and maintain them to ensure high availability and reliability.
– Collaboration: Collaborate with data scientists and software engineers to integrate AI/ML components into our products and services.
– Research: Stay up-to-date with the latest advancements in AI/ML and contribute to research efforts to enhance our solutions.
– Documentation: Create comprehensive documentation for models, algorithms, and processes to ensure knowledge sharing and reproducibility.
– Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field.
– Proven experience in developing and deploying machine learning models in real-world applications.
– Strong knowledge of machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn).
– Solid understanding of data structures, algorithms, and statistical concepts.
– Experience with data preprocessing, feature engineering, and model evaluation.
– Experience with working on large language models (LLMs) and Generative AI models is a plus.
– Experience with working on cloud tools such as AWS SageMaker is a plus.
– Excellent problem-solving skills and the ability to work in a collaborative team environment.
– Strong communication skills to convey complex technical concepts to non-technical stakeholders.