ML Engineer: Production LLMs for EDA (Onsite in SJ)

raydar; San Jose (CA); On-site; USD 180,000 - 350,000; Full time

Benefits offered by this job

Equity

Relocation support

Job summary

Raydar is seeking a Machine Learning Engineer in San Jose to own the modeling side of a software platform. You will adapt large language models for technical tasks, build data pipelines, and develop test suites to ensure model quality.

You will collaborate with researchers and systems engineers to ship new models into production. Ideal candidates have hands-on ML experience with hardware design data, end-to-end model development, and a strong Python/PyTorch background.

Qualifications

• University degree in an engineering or computing discipline, ideally with an ML emphasis.

Responsibilities

• Adapt large language models to specialized technical tasks using supervised learning and reinforcement-based methods.
• Create and maintain data flows that feed training, including sourcing, cleanup and artificial data creation.
• Develop test suites and scoring methods to measure model accuracy and reliability on realistic tasks.
• Plan and run experiments, study outcomes, and refine approaches in short cycles.
• Partner with researchers, systems engineers and domain specialists to ship new models into production.
• Track new academic and open-source developments and bring useful ideas into the team's models.

Skills

Python

PyTorch

LLM libraries

Data pipelines

Experiment design

Production ML

Reinforcement learning

C/C++ familiarity

Education

Engineering or Computing degree (ML emphasis)

Tools

CUDA

GNN frameworks

Job description

Raydar is seeking a Machine Learning Engineer in San Jose to own the modeling side of a software platform. You will adapt large language models for technical tasks, build data pipelines, and develop test suites to ensure model quality.

You will collaborate with researchers and systems engineers to ship new models into production. Ideal candidates have hands-on ML experience with hardware design data, end-to-end model development, and a strong Python/PyTorch background.