Remote Masters Computer Science Jobs in Michigan

Hundreds of engineers build vehicle software on our platform every day. This role leads the next step in how our model-based pipeline scales: generation, validation, and quality gates that run reproducibly, share a common cache, and return feedback fast. You set the technical direction and build it. 

Our engineers do outstanding authoring work, and that craft stays firmly with them. This role builds on that strength. It takes everything downstream of authoring — generation, validation, integration — onto a shared, reproducible, high-efficiency environment that returns results in seconds and gives engineers time back. You lead that evolution on both fronts: the platform mechanics and the ways of working that grow alongside them. 

You work at the intersection of model-driven development, build-system engineering, and cloud-native infrastructure. You set direction, author the rules the team and its consumers rely on, and hold a high quality bar. 

 What you'll own: 

• Models as first-class inputs in the dependency graph. Authored artifacts become versioned, buildable nodes alongside every other source, so generation and  integration become properties of the graph itself. 

• Build-system integration for model-based workloads: action contracts, hermeticity, determinism, and cache-key correctness that hold up at platform scale. 

• The remote-execution strategy for license-bound and compute-heavy workloads: worker pool design, license-aware scheduling, and the growth toward shared,  observable, cloud-scale infrastructure. 

• Cache economics for the most demanding build actions. You design so expensive work is computed once and reused across every developer and CI job that shares the same inputs. 

• Model quality and generated-code quality standards translated into executable, build-integrated gates that propagate through the dependency graph and give teams confidence continuously. 

• The adoption path. Engineers keep authoring in the interfaces they already trust, and every step after that runs on the most efficient environment available — desktop or Linux, local or cloud. You make the faster path the natural one and bring people with you. 

• Supplier roadmap conversations. You partner with tool providers on stronger headless execution, reproducibility, and integration contracts, with the depth to make those conversations productive. 

• The team's technical direction on the model-based and build-platform boundary, through mentoring, design leadership, and shared standards. 

Why this role? 

This platform underpins functional safety-critical software, so architectural correctness sits at the center of everything we build. The role pairs real engineering depth with the chance to shape how a large, skilled organization works at its best. You will own a system hundreds of engineers rely on, set its direction, and see your decisions compound across the whole fleet. If that scope fits how you like to work, we would like to talk. 

Basic Qualifications:

• Bachelor's in Computer Science, Computer Engineering or related field. 
• Minimum of 5 years of overall software engineering experience 
• Deep model-driven development experience for embedded software, proven through delivery. 
• Build-system engineering: dependency graphs, action sandboxing, cache-key stability, build rule authorship. You have built infrastructure others depend on and kept it sound as it grew. 
• Remote execution and cloud infrastructure: worker scheduling, content-addressed caching, cross-platform output sharing, and cost and saturation reasoning. You are comfortable across Linux and cloud environments. 
• Strong grounding in automotive software quality and functional safety standards, enough to define what the platform must prove and to align with safety owners. 
• A track record of evolving how teams work as well as what they run. You have moved a team onto a shared, reproducible environment and left them glad they made the move. 
• The judgment to invest time in getting foundational decisions right. 

Preferred Qualifications:

• Masters or PhD in Computer Science, Computer Engineering or related field, functional safety tool qualification, experience in software and/or tech industry, embedded configuration management and generated-artifact traceability, Kubernetes or equivalent fleet orchestration, enterprise InnerSource governance.