Staff ML Engineer: End-to-End AI Silicon & Security

Lorven Technologies Inc.; San Jose (CA); On-site; USD 150,000 - 190,000; Full time

Job summary

Lorven Technologies Inc. is seeking an ML engineer who works across the full stack—from model to silicon—optimizing training and inference on GPU/AI accelerators and adapting models to chip constraints.

You’ll move between algorithm work, systems software, and hardware-in-the-loop infrastructure to ship AI features end-to-end. This role offers rare exposure to AI silicon, from model design to production ready NPU cores, with collaboration across RTL, firmware, and QA teams to ensure reliable

Qualifications

• 5–7+ years hands-on AI/ML experience; Master's required, PhD preferred.
• Hands-on experience with AI/ML infrastructure and performance — GPU clusters, distributed training, inference-serving optimization, MLOps pipelines.
• Model / algorithm development experience — designing, training, and evaluating ML models.
• Experience taking models into production — feature engineering, data pipelines, deployment.
• AI chip / hardware‑aware ML experience — optimizing inference engines for a specific chip, or adapting model architecture/quantization to chip constraints.

Responsibilities

• Optimize training and inference performance across GPU and AI‑accelerator infrastructure, including MLOps pipelines.
• Design, train, and evaluate ML models (deep learning, LLM, CV, or recommendation systems) and take them into production.
• Harden and extend NPU cores into production silicon.
• Build or optimize inference engines and serving runtimes against real hardware constraints — latency, memory, and power.
• Work below the application layer where needed — BMC firmware, embedded Linux, or RTOS — so AI features run reliably on real systems.
• Build automated test/verification harnesses that close the loop for AI‑assisted RTL/DV, hardware bring‑up, or manufacturing test.
• Apply ML to security — AI‑driven log/intrusion analysis, AI‑assisted penetration testing, or firmware/hardware security work.
• Collaborate closely with RTL/hardware, firmware, and QA teams to ship AI features end‑to‑end, from training through deployment and monitoring.

Skills

AI/ML experience

MLOps

Model development

Production deployment

Education

Master's degree

PhD preferred

Tools

Zephyr RTOS

BMC firmware

Embedded Linux

Job description

Lorven Technologies Inc. is seeking an ML engineer who works across the full stack—from model to silicon—optimizing training and inference on GPU/AI accelerators and adapting models to chip constraints.

You’ll move between algorithm work, systems software, and hardware-in-the-loop infrastructure to ship AI features end-to-end. This role offers rare exposure to AI silicon, from model design to production ready NPU cores, with collaboration across RTL, firmware, and QA teams to ensure reliable