Job Summary:

We are hiring a Senior Software Engineer, based in the United States, to enhance the reliability, performance, and scalability of our production AI systems. We value clear thinking, incremental improvement, and engineers with real production incident experience. This role focuses on understanding, refining, and strengthening existing distributed services across application, database, and container orchestration layers. You will collaborate with ML researchers to make our systems more robust, maintainable, flexible, and scalable. This is a remote position but requires the ability to travel to the MixMode headquarters in Santa Barbara for in person meetings a few times a year.

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

Our Interview Process:

Our interview process focuses on real-world production experience and practical systems thinking. We assess how you reason about distributed systems, refactor existing code, and operate under real constraints—not abstract puzzles. We support the use of AI tools in our development, but we want to understand your capabilities first. No AI tools will be allowed for remote interviews early in the process.

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

We are open to hiring great talent who may have qualifications above or below those specifically listed in this job description. Pursuant to California law, we must display the pay range for this job. Since we are willing to hire within a broad spectrum of qualifications, we also reflect a broad pay range. The base hourly range that we are targeting for this position is $150,000-$210,000 though we can adjust based on individual qualifications. Individual salary is determined by qualifications, role, level, and location.