Senior ML Engineer: AI Hardware & MLOps (Onsite, San Jose)

ValueBase Consulting; San Jose (CA); On-site; USD 96,000 - 110,000; Full time

Job summary

ValueBase Consulting in San Jose, CA is hiring a Senior Staff Machine Learning Engineer for an onsite contract role. You will work at the intersection of AI and security processor hardware, spanning model development through silicon/NPU enablement, inference engines, and end-to-end MLOps deployment.

You’ll optimize hardware-aware performance and verification workflows to ensure AI features run reliably on real systems.

Qualifications

• 8-10+ years of hands-on AI/ML experience; Master’s degree required; PhD preferred.
• Hands-on experience with AI/ML infrastructure and performance, including GPU clusters and distributed training.
• Experience taking models into production, including feature engineering, data pipelines, and deployment.

Responsibilities

• Optimize training and inference performance across GPU and AI-accelerator infrastructure, including MLOps pipelines.
• Design, train, and evaluate ML models, including deep learning, LLMs, computer vision, or recommendation systems; drive to production.
• Harden and extend NPU cores into production silicon with RVV/tensor core considerations.
• Build or optimize inference engines and serving runtimes for real hardware constraints focusing on latency, memory, and power.
• Work with BMC firmware, embedded Linux, or RTOS to ensure AI features run reliably on hardware.
• Create automated test and verification harnesses supporting RTL/DV, hardware bring-up, or MFG tests.
• Apply ML to security uses cases such as AI-driven log or intrusion analysis and firmware security work.
• Collaborate with RTL/hardware, firmware, and QA teams to ship AI capabilities end-to-end.

Skills

AI infrastructure

GPU clusters

MLOps pipelines

Model development

Production deployment

Security-aware ML

Education

Master’s degree in a relevant field

PhD preferred

Tools

NPU hardware

RVV/tensor core

CoralNPU

Job description

ValueBase Consulting in San Jose, CA is hiring a Senior Staff Machine Learning Engineer for an onsite contract role. You will work at the intersection of AI and security processor hardware, spanning model development through silicon/NPU enablement, inference engines, and end-to-end MLOps deployment.

You’ll optimize hardware-aware performance and verification workflows to ensure AI features run reliably on real systems.