Principal Software Engineer

Midjourney; San Francisco (CA); On-site; USD 180,000 - 260,000; Full time

Job summary

Midjourney in San Francisco seeks a technical lead for the scanner platform, owning system architecture, codebase structure, and long-term maintainability. You will drive core runtime foundations and reliability across distributed components.

You will build observability, collaborate with hardware and ML teams, and guide complex refactors without slowing progress. The role demands deep software architecture experience, strong Python and concurrency skills, and a track record of shipping

Qualifications

• Deep software architecture experience for real-world systems.
• Strong Python and concurrency background (asyncio, multiprocessing).
• Track record of shipping systems that are observable, debuggable, and resilient.
• Strong technical leadership: clarity, pragmatic trade-offs, and mentoring.

Responsibilities

• Act as the technical lead for large parts of the scanner platform: system architecture, codebase structure, and long-term maintainability.
• Own core runtime foundations: distributed control, state management, fault handling, and reliability.
• Drive engineering rigor: testability, code quality, review standards, performance regression prevention, and release processes.
• Build robust observability: logs, metrics, traces, and replayable diagnostics (with privacy constraints).
• Collaborate with hardware and recon/ML teams to define interfaces, data contracts, timing/synchronization, and failure modes.
• Lead complex refactors (e.g., message passing / RPC boundaries, modularization, concurrency model) without halting forward progress.

Skills

Python

Concurrency

System architecture

Technical leadership

Tools

gRPC/Protobuf

CI/CD

Job description

• Act as the technical lead for large parts of the scanner platform: system architecture, codebase structure, and long-term maintainability.
• Own core runtime foundations: distributed control, state management, fault handling, and reliability.
• Drive engineering rigor: testability, code quality, review standards, performance regression prevention, and release processes.
• Build robust observability: logs, metrics, traces, and replayable diagnostics (with privacy constraints).
• Collaborate with hardware and recon/ML teams to define interfaces, data contracts, timing/synchronization, and failure modes.
• Lead complex refactors (e.g., message passing / RPC boundaries, modularization, concurrency model) without halting forward progress.

What you'll do

• Act as the technical lead for large parts of the scanner platform: system architecture, codebase structure, and long-term maintainability.
• Own core runtime foundations: distributed control, state management, fault handling, and reliability.
• Drive engineering rigor: testability, code quality, review standards, performance regression prevention, and release processes.
• Build robust observability: logs, metrics, traces, and replayable diagnostics (with privacy constraints).
• Collaborate with hardware and recon/ML teams to define interfaces, data contracts, timing/synchronization, and failure modes.
• Lead complex refactors (e.g., message passing / RPC boundaries, modularization, concurrency model) without halting forward progress.

What we're looking for

• Deep software architecture experience for real-world systems: robotics, instrumentation, medical devices, or other complex distributed products.
• Strong Python and concurrency background (asyncio, multiprocessing, profiling, performance engineering).
• Track record of shipping systems that are observable, debuggable, and resilient.
• Strong technical leadership: clarity, pragmatic trade-offs, and mentoring.

Useful experience

• Building but rock-solid systems: clear interfaces (gRPC/protobuf or equivalent), strong state modeling, and failure handling.
• High-leverage engineering habits on a lean team: good tests, CI, reproducible dev environments, and fast code review.
• Practical performance + concurrency work in Python (asyncio, profiling, multiprocessing) and comfort debugging distributed behavior.
• Security-minded device software: safe defaults, encrypted data paths, and disciplined handling of PII/PHI.
• Operational thinking: remote updates/management, excellent logging, and diagnostics that make real hardware debuggable.