As a Senior Data Engineer, youβll be the technical backbone of the data layer that powers Daylight β ApartmentIQβs revenue-management product that delivers real-time rent recommendations to property managers. Youβll design, build, and own the ingestion framework that pulls operational data from a variety of property-management systems, transforms it into analytics-ready models, and serves it to the machine-learning workflows that forecast demand and optimize pricing.
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As an AI/Machine Learning Engineer, you will lead the development and deployment of advanced machine learning models and AI solutions. You will collaborate with cross-functional teams to drive innovation and deliver impactful AI-driven products. Youβll apply AI/ML expertise to solve meaningful challenges in federal programs, driving innovation in healthcare, veteransβ services, and more.
As a Data Scientist, you will develop and implement advanced fraud detection models to protect customersβ business from fraudulent activities. As an early member in the ML team you will have great impact in building out our ML stack. Responsibilities include developing fraud detection systems and processes, analyzing data to improve fraud prevention strategies, and optimizing existing models.
The data scientist will lead a cross-functional team to develop an AI-powered solution that breaks down barriers to healthcare. By leveraging cutting-edge technologies, including LLMs from Google and Anthropic, the data scientist will analyze patient information and automatically generate accurate responses to complex forms. The ideal candidate will combine strong technical expertise with excellent communication skills and a passion for continuous learning.
As an ambitious and talented Senior Data Scientist joining our growing team, you will have previous experience of deploying machine learning solutions to solve complex business problems. You will be adept working through the full development pipeline and comfortable working in a start-up like environment.
An AI model trainer brings specialised knowledge in developing and fine-tuning machine learning models, ensuring models are accurate, efficient, and tailored to specific needs, significantly enhancing our data management and analytics capabilities. Expertise in Model Development, Quality Assurance, Efficiency and Scalability, and Production ML Monitoring & MLOps are crucial for this role.
As a Staff Machine Learning Scientist, you will lead the development of customer-facing, production deployed Machine Learning capabilities within the payments space; requiring a strong understanding of ML development methodology and modern MLOps practices and techniques. Additionally, this role will help inform the technical trajectory of our ML ecosystem and drive excellence in our ML development practices.
As a Staff Machine Learning Scientist within our Data+ML organization, you will lead the development of customer-facing, production deployed Machine Learning capabilities to domain problems within the payments space. This role will straddle both engineering and science concerns requiring a strong understanding of ML development methodology and theory, and modern MLOps practices and techniques. Additionally, this role will help inform the technical trajectory of our ML ecosystem.
As our ML Engineer, youβll be part of a small, focused team building the foundation of our ML systems, working on impactful product features, collaborating with engineers and analysts, and having the freedom to experiment and learn to unlock massive value for the customers. You will develop and deploy ML models to power features like product recommendations, personalization, and demand forecasting.
We're looking for a talented Data Scientist with expert Python skills and experience in processing large amounts of data to join the team. You'll be a key player in designing, building, and making their main data pipelines and ML systems (that power our advanced analytics and machine learning models) able to handle more. You'll work closely with data scientists and engineers to create strong, efficient, and scalable systems.