Wayve Senior Machine Learning Engineer at Wayve building and leading the Vehicle Software SRE team focused on reliability of autonomous vehicle software. Responsible for team building, reliability strategy, and production readiness.
Responsibilities
As SRE Manager, you'll build the Vehicle Software SRE team from the ground up — defining its charter, hiring its founding engineers, establishing the operating model, and creating the technical strategy that makes reliability a first-class property of the software running on our vehicles.
You'll work in a production environment unlike most: a globally distributed fleet of autonomous vehicles operating at the intersection of software, hardware, networking, sensors, and the physical world. Failures are often intermittent, hard to reproduce, and distributed across ownership boundaries. You'll move reliability upstream — from reactive field support to prevention through architecture, automation, observability, and disciplined production readiness.
You'll embed your team within Vehicle Software, partnering with product teams who retain ownership of what they build while your team provides the reliability engineering, standards, and leverage that help them operate fleet-critical software safely at scale. You'll stay hands-on throughout — writing code, reviewing critical designs, and leading the investigations that matter most.
The systems you help harden will connect Wayve's AI to physical vehicles and underpin the transition from engineering fleets to commercial operations. Few engineering leadership roles offer this combination of zero-to-one team building, deep systems work, and direct influence on the safety and scalability of autonomous mobility.
Team building & leadership :Build and lead a new SRE team from the ground up, staying hands-on as a player-coach on the team's most consequential work.
Reliability strategy: Own technical direction for vehicle software reliability across deployment, service health, telemetry, and diagnostics; define what production-ready means at Wayve.
Production readiness: Define SLIs, SLOs, and error budgets for fleet-critical workflows; drive release criteria, automated gates, rollback strategies, and fault-injection practices across Vehicle Software.
Observability & tooling: Design and implement the observability and automation that shortens the path from vehicle symptom to root cause, cuts the manual toil between failure and fix, and shapes systems for robustness, recoverability, and debuggability.
Incident response: Lead investigations into complex failures, ensure every incident produces a durable fix, and strengthen on-call practices and escalation paths across service-owning teams.
Mentorship & communication: Mentor engineers and emerging leaders, and give senior leadership the clarity on reliability health, risks, and investment they need to make good decisions.
Qualification
Proven experience with SLOsA track record of turning ambiguousCalm and structured during incidentsExperience with autonomous vehiclesKnowledge of onboard computeWhat success looks likeIn the first 90 days
Required
8+ years building and operating production software systems with strong depth in SRE, production engineering, platform engineering, embedded systems, or robotics, and a recent track record of writing production-quality code and leading architecture reviews across Linux-based, distributed, or hardware-software systems.
3+ years in people leadership with a track record of hiring, coaching, and growing engineers across levels while staying actively engaged in coding, design, and code review; experience forming a new team or capability from scratch is a strong plus.
Proven experience with SLOs, error budgets, production-readiness standards, observability, incident management, postmortems, and toil-reduction programmes, with measurable outcomes to show for it.
A track record of turning ambiguous, cross-functional problems into clear ownership, sequenced plans, and reliable delivery without relying on formal authority.
Hands-on experience building production software, automation, and diagnostic tooling in C++, Rust, Python, or Go, with familiarity with CI/CD, release systems, telemetry pipelines, and modern observability tooling.
Calm and structured during incidents, with clear communication across software, hardware, operations, product, and executive stakeholders; a leadership approach grounded in ownership, blameless learning, and autonomy with accountability.
Experience with autonomous vehicles, robotics, automotive software, safety-critical systems, or cyber-physical products deployed into uncontrolled real-world environments.
Knowledge of onboard compute, sensors, middleware, vehicle networks, OTA deployment, data capture and offload, or multi-variant hardware-software integration.
Experience improving reliability through the transition from research and prototype systems to commercial, multi-market operations.
Experience partnering with fleet operations, field engineering, validation, hardware, or external vehicle and technology partners.
What success looks like
In the first 90 days, you have aligned the charter and ownership model, established a reliability baseline, mapped the highest-risk systems and workflows, defined the hiring plan, and personally contributed design, code, or tooling to deliver early reliability wins.
