Greetings, Future Homie!Join us at Homebase, where we are passionate about empowering small businesses to flourish. Our dynamic team is driven by empathy, urgency, and a bold approach that leads to meaningful outcomes. At Homebase, every team member contributes to elevating our standards, supporting each other, and celebrating our collective successes.We are not merely developing an application; we are fostering unstoppable teams. Are you ready to join us?Your Impact Begins HereAs a Platform Engineer, you will play a key role in designing and implementing components for our data and ML platforms. Your contributions will empower data engineering, data science, and product teams to create features driven by data and machine learning, ensuring that our systems are scalable, reliable, and seamlessly integrated.Architect, develop, and enhance the ingestion processes for large volumes of both structured and unstructured data from a variety of sources.Facilitate data architecture transformation initiatives on Databricks, promoting scalable and efficient systems.Lead the design and implementation of platform components for training, deploying, and monitoring machine learning models in production environments.Provide insights into industry best practices, tools, and technologies in the field of machine learning engineering.Champion continuous enhancements of data and ML workflows through automation and innovative solutions.Own projects end-to-end, ensuring successful delivery from planning to execution.Collaborate with cross-functional teams to gather business requirements and develop effective technical solutions. Key to Your Success - These experiences and strengths will position you for success:Over 5 years of experience in software development, with a focus on data and machine learning.Proficient in SQL, Python, and Databricks.Experience with Airflow, Kafka, and Redshift.Strong skills in data modeling and database design.Expertise in building and deploying machine learning models, including language models.Experience in creating model serving pipelines for batch, streaming, and real-time inference.Demonstrated ability to work collaboratively in a fast-paced environment.
Feb 6, 2026
