Senior software engineer building scientific computing and ML systems for KoBold Metals, which uses AI and novel sensors for mineral exploration. Developing scalable pipelines and tooling across scientific, geophysical, and hardware data.
About the role
- Embedded Software Developer in Ford's product development team for next-gen connected vehicles. Collaborating on software architecture and engineering initiatives supporting vehicle platforms.
Responsibilities
- Contribute to software architecture enablement and advanced engineering initiatives supporting connected vehicle platforms
- Work closely with cross-functional teams to design, develop, and improve embedded, testing, middleware, platform engineering, and AI Ops solutions
- Strengthen the way software is built, reviewed, validated, and delivered
- Conduct architecture, design, code, and FMEA reviews as a representative of the architecture team; produce specific, actionable findings
- Identify gaps in requirements, interfaces, or integration assumptions early; surface them clearly to architects and stakeholders
- Contribute to CI/CD pipelines, static analysis configuration, and quality tooling that teams rely on daily
Requirements
- Bachelor's Degree in Computer Science, Computer Engineering or a related discipline
- 3-5 years of hands-on experience C++ development for high-level OS environments (Linux or QNX) and C development for MCU or bare-metal systems
- 3-5 years of experience with embedded systems
- Practical AUTOSAR experience (Classic AUTOSAR, Adaptive AUTOSAR, or both)
- Experience building and maintaining CI/CD scripts, pipelines, and development flows
- Demonstrated contribution to a team engineering ecosystem: internal tooling, shared scripts, AI-assisted workflows, or developer productivity improvements
- Experience with embedded networking, modem-related software, or MCU-based systems (even better)
- Hands-on programming in C++ and Python; familiarity with one or more of AUTOSAR C, Rust, or Node.js (even better)
- Expert-level contributions to optimizations, memory management, and reliability improvements in a major product embedded codebase (even better)
- Familiarity with AI Ops or AI-enabled engineering: pipeline automation, observability, operational analysis, agent-based tooling, or retrieval-based solutions (even better)
- Experience leading or contributing to design reviews, code reviews, and software quality improvement activities (even better)
- Understanding of software development processes such as ASPICE, FMEA, static analysis, and the V-model (even better)
- Familiarity with automotive cybersecurity and safety concepts such as ISO 21434, UNECE regulations, or ISO 26262 is an asset (even better)
Benefits
- Annual Compensation bonus program
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