Qualifications

• Strong generalist software engineering skills across backend systems, APIs, cloud infrastructure (GCP, AWS, or Azure), and modern frontend frameworks.
• Experience deploying and operating ML systems in production, preferably in diverse or customer-controlled environments.
• Familiarity with containerization, orchestration, and infrastructure-as-code tools (e.g. Kubernetes, Docker, Terraform).
• Ability to engage directly with customers, scoping ambiguous problems and building demos under time pressure.
• Background in scalable model serving and deployment architectures, along with associated systems.
• Demonstrated ownership of deliverables from requirements gathering to autonomous execution.

Responsibilities

• Build and operate the production systems that deliver model predictions to customers around hard real-time deadlines, ensuring reliability from cost efficiency to incident response.
• Design and construct the product surface, including backend APIs, data delivery integration patterns, and frontend dashboards to make predictions actionable.
• Oversee the packaging, security, observability, and upgrade processes for deploying products into customer environments, including cloud and on-premises settings.
• Create engaging product demos and prototypes for prospective customers, iterating rapidly alongside go-to-market efforts.
• Engage directly with customer environments when required, integrating their data and systems while shipping solutions on-site, translating insights into product requirements.
• Design tooling and playbooks that enable solutions to be generalized across various customers.

Benefits

• Flexible working hours to accommodate diverse schedules.
• Opportunities for professional development and training in emerging technologies.
• Dynamic work environment that encourages innovation and creativity.
• Access to the latest tools and resources to excel in your role.
• Collaborative culture with an emphasis on teamwork and shared success.