Data Product Engineer, Sense Street

• Strong software or data engineering background (Python, SQL, cloud platforms)
• Experience with data pipelines, backend systems, and APIs (ETL/ELT, microservices)
• Familiarity with distributed systems, cloud environments (AWS/GCP/Azure), and CI/CD
• Interest in working closely with ML engineers and AI-powered systems
• Willingness to think about data accessibility and usability, not just infrastructure

Desirable

• This is a new and evolving role, ideal for a data or software engineer who wants to work at the intersection of data engineering, ML infrastructure, and product integration
• We don’t expect you to have experience with all of these—this role is a great opportunity for someone who wants to grow into and shape the intersection of AI, data, and product development
• You’ll collaborate closely with ML engineers, data scientists, and product & UX design to bring AI models into production, develop robust data infrastructure, and contribute to how data is accessed and used—whether through APIs, internal tools, or analytics interfaces
• If you enjoy building scalable data solutions while thinking about how they fit into the bigger picture, this role offers an exciting challenge
• Build and maintain scalable data pipelines to support AI/ML workloads
• Develop APIs and backend services that integrate AI models into production systems
• Work with ML engineers to deploy and optimize AI models in real-world applications
• Contribute to architecture decisions that shape our AI/ML infrastructure
• Think about how data is accessed and used, including internal tools, dashboards, and analytics interfaces
• Implement monitoring, observability, and data reliability best practices