Jobs / United States / Renesas Electronics America INC
Senior Staff Application Technology Architect – Edge Artificial Intelligence & Machine Learning
Renesas Electronics America INC · 🇺🇸 Austin, TEXAS, US
Sponsorship verdict
Sponsorship possible
One solid signal, not two — worth applying, and worth asking about sponsorship early.
- Employer is on a government sponsor recordThe US Department of Labor certified 56 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 18 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
- The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
- No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
- What Renesas Electronics America INC paid sponsored hires in similar roles6 certified filings for “Sr. Staff Application Engineer” (Electronics Engineers, Except Computer) in TX: $132k–$180k, median $167k. Most were filed at wage level IV (67%) — 4 lottery entries, ≈61% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).
- Confirmed live todayWhen a source last listed this job as open.
US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).
A verdict summarises public evidence; it is not legal advice and never a guarantee — the employer and the immigration authority decide. Sign in to factor in where you can already work.
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Sponsor Radar — Renesas Electronics America INC
The US Department of Labor certified 56 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 18 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
Past sponsorship or register membership never guarantees sponsorship for this vacancy or for you. Full Sponsor Radar for Renesas Electronics America INC →
About the role
About the Role We are looking for an experienced and visionary Edge AI Architect to define, drive, and evolve artificial intelligence and machine learning technologies across a broad range of intelligent embedded and edge computing solutions. In this role, you will serve as a technical authority for AI and machine learning, bridging advanced algorithms, sensor analytics, edge computing, and semiconductor technologies. You will collaborate with product groups, system architects, software teams, and strategic customers to develop innovative AI-enabled solutions that deliver differentiated value across multiple market segments. Your work will help shape the company's AI strategy, accelerate adoption of edge intelligence, and enable next-generation intelligent systems through advanced machine learning, signal processing, perception, and data analytics technologies. Key Responsibilities • Define and own AI/ML technology architectures spanning embedded systems, edge computing, cloud-connected systems, and intelligent sensor solutions. • Translate customer challenges, market opportunities, and technology trends into AI solution architectures and technology roadmaps. • Drive development of reusable AI frameworks, software architectures, inference pipelines, model-deployment methodologies, and reference implementations. • Lead the evaluation, development, and adoption of machine learning, deep learning, foundation-model, and agentic-AI technologies. • Define architectures for: • Sensor intelligence • Signal processing • Computer vision • Anomaly detection • Predictive analytics • Sensor fusion • Autonomous decision making • Multimodal AI systems • Drive hardware/software partitioning across MCUs, MPUs, AI accelerators, NPUs, DSPs, FPGAs, and cloud resources. • Define efficient deployment strategies for AI workloads on resource-constrained embedded platforms. • Evaluate and optimize AI models for accuracy, latency, memory footprint, power consumption, and cost. • Collaborate closely with product groups, software teams, system architects, and research partners to integrate AI capabilities into future solutions. • Support strategic customer engagements and act as a trusted advisor on AI architecture and deployment. • Monitor advances in AI/ML research and identify opportunities for product differentiation and innovation. • Contribute to AI reference architectures, technical papers, application notes, patents, and ecosystem initiatives. • Provide mentoring and technical leadership to engineering teams across the organization. • Master's or Ph.D. degree in Computer Science, Applied Mathematics, Artificial Intelligence, Electrical Engineering, Physics, Data Science, or a related field. • 10+ years of experience in AI/ML, advanced analytics, signal processing, computer vision, or intelligent embedded systems. • Proven track record as an AI Architect, Principal AI Engineer, Chief Architect, AI Research Lead, or equivalent technical leadership role. Proven Expertise In: Machine Learning, Deep Learning, Statistical Modeling, Signal Processing, Computer Vision, Sensor Analytics, Data Fusion, Pattern Recognition, Predictive Analytics, Time-Series Analysis, Explainable AI, Edge AI Strong Experience With: PyTorch, TensorFlow, ONNX, ML model optimization, Data pipelines, AI deployment frameworks Strong Understanding Of: Embedded systems, Edge computing platforms, Heterogeneous compute architectures, MCUs, MPUs, NPUs, DSPs, and AI accelerators, Performance, power, and memory optimization Nice to Have • PhD in Applied Mathematics, Machine Learning, Signal Processing, Computer Vision, or related discipline • Experience developing patented AI technologies or algorithms • Publications in AI,