Member of Technical Staff - Product Engineering

About the role

This position involves transforming advanced research models into practical, customer-facing products. You will build and maintain the systems that deliver predictions reliably and on time. The work spans from backend infrastructure to user interfaces, ensuring our AI solutions are deployable and valuable in diverse environments. You will own the full lifecycle of production features, translating algorithmic concepts into robust services that meet strict operational standards. The role requires deep collaboration with research and product teams to align technical implementation with user needs and business goals. You will be responsible for designing systems that balance performance, cost, and maintainability under real-world constraints. Your contributions will directly shape the reliability and usability of our platform for customers across different deployment scenarios.

Key facts

What you'll do

• Develop and manage production systems that deliver model predictions to clients within strict real-time constraints, overseeing reliability, cost, monitoring, and incident response.
• Create the complete product interface, including backend APIs, data delivery methods, integration patterns, and frontend dashboards for actionable predictions.
• Manage the packaging, security, monitoring, and update mechanisms for deploying our product in various client environments, such as cloud, VPC, on-premise, and restricted networks.
• Build product demonstrations and prototypes for potential customers, collaborating closely with the go-to-market team.
• Work directly with customers when necessary, integrating with their data, deploying solutions on-site, and translating insights into research and product requirements.
• Develop tools and procedures that allow customer-specific solutions to be applied more broadly.
• Design and implement scalable serving architectures that handle variable workloads while maintaining predictable performance and latency.
• Collaborate with infrastructure and platform teams to optimize resource utilization, cost efficiency, and system resilience.
• Implement observability practices, including logging, metrics, and tracing, to ensure transparency and rapid troubleshooting in production.
• Partner with data scientists to operationalize experimental models, ensuring they meet production standards for scalability and maintainability.
• Define and enforce deployment pipelines that support continuous integration and delivery for machine learning systems.
• Evaluate emerging infrastructure technologies and determine their applicability to our product stack and customer requirements.
• Document system behaviors, interfaces, and operational procedures to support long-term maintenance and knowledge transfer.
• Support the development roadmap by estimating effort, identifying dependencies, and coordinating cross-functional initiatives.
• Act as a technical owner for assigned features, ensuring alignment between implementation details and desired outcomes.

Requirements

• Possess strong generalist software engineering abilities across the entire stack, including backend systems, APIs, cloud infrastructure (GCP, AWS, or Azure), and current frontend frameworks.
• Have experience deploying and operating machine learning systems in production, particularly in varied or customer-managed settings.
• Be familiar with containerization, orchestration, and infrastructure-as-code tools like Kubernetes, Docker, and Terraform.
• Be comfortable interacting directly with customers, defining unclear problems, creating demos under pressure, and representing the company technically.
• Have a background in scalable model serving and deployment architectures, along with their supporting systems.
• Be capable of owning deliverables from initial requirements through independent execution.
• Demonstrate proficiency in at least one modern programming language relevant to backend and infrastructure development.
• Show a track record of building and maintaining reliable distributed systems in production environments.
• Understand networking, security fundamentals, and data handling best practices in cloud-based applications.
• Exhibit strong problem-solving skills and the ability to debug complex issues in live systems.
• Communicate effectively with both technical and non-technical stakeholders during collaborative discussions and planning sessions.
• Adapt quickly to changing priorities and evolving product requirements while maintaining high standards of quality.
• Take initiative in identifying potential improvements to system performance, reliability, and developer experience.
• Commit to following established processes while also contributing feedback for iterative refinement of workflows.

Practical notes

This role is based in San Francisco and operates on a full-time basis. The position reports to the Infrastructure team and requires close coordination with product, research, and customer-facing functions. There are no specific compensation details provided in the source material. The successful candidate will engage in hands-on technical work that spans the entire software development lifecycle, from initial design through deployment and ongoing operations. Travel requirements, if any, are not specified in the available information. Candidates must be authorized to work in the United States without sponsorship for this position. The hiring timeline is not detailed, but interested applicants are encouraged to submit materials promptly. No additional restrictions or preferences are outlined beyond those described in the requirements and key facts sections.