MixMode
Sr. Software Engineer-AI Reliability
Rol remoto de Site Reliability Engineer con fit claro de ubicación del candidato.
Publicado16 jul 2026
Países elegibles1 país aceptado
Señal de senioritySenior
Modelo de trabajoRemoto
Ubicaciones aceptadas para candidatos
Estados Unidos
Resumen del rol
Sr. Software Engineer-AI Reliability
Requisitos y responsabilidades
Contenido del rol extraído en secciones para revisar más rápido.
What you’ll be doing (responsibilities):
- Own the reliability, performance, and operational health of production AI services
- Refactor and harden existing systems to improve resilience, clarity, and maintainability
- Diagnose and resolve issues across distributed services, data pipelines, and storage layers
- Design and implement monitoring, alerting, and debugging tools for high-availability systems
- Partner with researchers and engineers to productionize predictive systems at scale
- Establish best practices for testing, deployment, capacity planning, and incident response
- Contribute to incident response and postmortems, driving continuous improvement
What you’ll need to bring (qualifications):
- Ability to travel to our office in Santa Barbara, CA, a few times per year
- 7+ years of professional software engineering experience
- Strong proficiency in Python and at least one JVM language (Java, Scala, Kotlin)
- Proven experience designing, building, and operating distributed systems in production
- Strong understanding of service architecture, concurrency, resource management, and distributed failure modes
- Experience operating Kubernetes deployments
- Strong experience with relational databases, including query performance analysis, indexing, and connection management
- Demonstrated ability to diagnose and resolve performance, scalability, and reliability issues across system layers
- Experience implementing automated testing and production observability (logging, metrics, tracing)
- Experience collaborating with ML or data science teams (deep ML expertise is not required)
- Ability to improve system architecture and engineering practices through design, code review, and mentorship
The process includes:
- Conversations about systems you’ve personally owned, improved, and operated in production
- A live refactoring and testing exercise in your choice of Java, Kotlin, or Scala, centered on improving existing code without changing behavior
- A distributed systems discussion covering performance, state management, failure modes, and debugging under load
- An ML production discussion focused on stabilizing and operating model-driven systems in real environments
- The final stage of our interview process includes an in-person conversation at our Santa Barbara office, focused on senior-level ownership, judgment, and technical leadership
Details
- Remote-First Work Culture
- Healthcare (Medical, Dental, Vision, Accident)
- Basic & Voluntary Life and AD&D
- Flexible Spending Account (FSA)
- 401(k) with Employer Match
- Paid Holidays & Flexible Paid Time Off (PTO)
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