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Strong employer brand, metro location, and mid-level engineering/ML experience increase applicant competition.
Embedded ML and firmware work is highly domain-specific to electrification and hardware-integrated systems.
Requires PhD/M.Tech, explicit 4 years experience, embedded ML/firmware skills, and specific tech stack.
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Research and develop embedded data analytics and AI prototypes, focusing on predictive maintenance and ML algorithms for embedded/edge devices.
Conduct unit, integration, and system testing to ensure software quality and facilitate integration of R&D outcomes into products.
Drive intellectual property creation, monitor technology developments to influence R&D projects, and manage firmware development activities including risk and coordination with suppliers.
PhD or M.Tech in Computer Science, Electronics, Electrical Engineering, Embedded Systems or related field with 4 years hands-on experience and at least 2 project cycles.
Proficiency in C/C++/Python/MATLAB and knowledge of TensorFlow/Rust with solid computer science fundamentals.
Experience in predictive maintenance, classical ML approaches and deep learning suitable for embedded/edge environments.
Experience with development infrastructure including Azure DevOps, CI/CD, git, build systems, unit testing, and debug tools.
Experienced in end-to-end embedded software development lifecycle with strong understanding of R&D project drivers and business relevance.
Comfortable working independently within R&D teams and collaborating cross-functionally including with suppliers and product management.
Capable of contributing technically and strategically to IP creation, innovation tracking and applying solution-focused development to embedded analytics projects.