Machine Learning Engineer

OCTOPYD • Full-time • Redwood City, CA, US • 5d ago

About the job

Why this matters

AI is reshaping every industry—and semiconductor design is next. At our partner company, you’ll work at the intersection of cutting-edge ML and hardware innovation, helping bring frontier models specialized for semiconductors into the hands of chip designers. From deploying optimized foundation models to building low-latency inference infrastructure, your work will define how engineers interact with intelligence. If you're excited to make research real and shape the future of design, this role is for you.

What you'll do

Fine-tune, evaluate, and deploy LLMs and foundation models for specialized chip engineering tasks.
Build scalable inference systems, agentic workflows, and RAG pipelines to support intelligent, interactive design tools.
Optimize model performance through batching, caching, quantization, and streaming to achieve sub-second latency.
Collaborate closely with AI scientists to operationalize experimental techniques and deliver robust, production-grade systems.
Contribute to architecture decisions around scalable, reliable ML infrastructure in a cloud-native environment.
Own the end-to-end lifecycle of ML features—from prototyping to deployment and observability in production.

What You Bring

2+ years of ML engineering experience, including a track record of shipping production ML systems.
2+ years of hands-on experience working with LLMs, including prompt tuning, fine-tuning, and evaluation.
Deep expertise in Python, PyTorch, and the surrounding ML tooling ecosystem.
Familiarity with orchestration frameworks and agentic workflows (e.g., LangChain, LlamaIndex).
Strong understanding of vector search, semantic embeddings, and RAG systems.
Solid grasp of scalable ML architecture and the principles behind high-availability inference systems.

Bonus Points

Experience working directly with ML researchers or in applied research settings.
Background in electrical engineering, chip design tools, or physical design flows.
Startup experience or contributions to high-velocity, cross-functional teams.
Open-source contributions to ML tooling or infrastructure projects.
Experience deploying models in cloud environments (e.g. AWS SageMaker, Bedrock, vLLM, or SGLang)

What it's like here

We’re a fast-moving AI startup with a collaborative, high-trust culture. You’ll work side-by-side with top engineers and scientists, translating cutting-edge research into real product impact. We value curiosity, speed, and precision—engineering systems that are elegant, pragmatic, and built to last. If you’re passionate about bringing frontier AI to the real world, you’ll feel right at home.

Logistics

This position is available in Silicon Valley’s Redwood Shores, CA and in Toronto, ON. We believe a mindmelt between engineers and scientists leads to our professional growth and to great products; we have a hybrid schedule with four days in office, one day remote. Cognichip accepts applications that need H1B transfer.

How to apply

Don’t meet every single requirement? Feel over-qualified? That’s okay—if you're excited about our mission, we’d still love to hear from you. We are growing fast and need a world class team of various experience levels.