
Silicon Engineer
Primary stack
Nice to have's
Job description
Silicon Engineer
San Francisco, CA
About Anthropic
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.
About the Role
Anthropic runs some of the largest AI training and inference workloads in the world, across multiple hardware platforms. We work from the chip level up with our silicon partners, and we are now deepening that investment by building a custom silicon team.
You will be one of a small number of people covering a large surface. We are opening searches across the key domains below, and we are interested in candidates whose center of gravity sits in any of them:
- Front-end design
- Pre-silicon verification
- Physical design
- Design for test
- Analog and mixed-signal
- Technology and foundry
- CAD and design infrastructure
- Packaging, signal integrity, and power integrity
This is a role for someone who has shipped silicon, has a realistic relationship with schedules, and is comfortable making consequential calls without a large organization behind them.
Key Responsibilities
- Take part in end-to-end activities for the program: strategy, specification, execution, and the technical bar.
- Write the specifications and interface definitions that others design against and keep them coherent as the architecture converges.
- Make and own directional calls: technology and IP selection, where we build versus buy versus license, and where we take design authority versus rely on partners.
- Build and share AI-assisted approaches to the code-like parts of your domain, and help the team learn what can genuinely accelerate.
- Contribute to the architecture and micro-architecture discussion from your domain's perspective, including the tradeoffs your area imposes on the rest of the chip.
- Partner with Anthropic's inference, performance, kernels, and infrastructure teams on hardware-software co-design, and with our hardware systems team on bring-up and integration.
- Support first-silicon bring-up and debug when it arrives, regardless of which domain you came in through.
Minimum Qualifications
- Deep, hands-on expertise in at least one silicon domain: front-end design, pre-silicon verification, physical design, design for test, analog and mixed-signal, technology and foundry, design infrastructure, or packaging and signal/power integrity.
- Direct personal contribution to silicon that taped out and shipped, with ownership you can speak to in detail.
- Working fluency in the domains adjacent to your own, sufficient to reason about chip-level tradeoffs outside your specialty.
- Experience working with external partners - ASIC houses, IP vendors, foundries, or test partners - including reviewing their work and holding a technical bar.
- Track record of owning directional technical decisions and their consequences, not only making recommendations.
- Practical experience using AI coding tools in your own work, and clear ideas about where they help and where they do not.
- Clear written and verbal communication, and experience driving alignment across teams and organizations.
- Comfort operating with high autonomy and little scaffolding on a highly dynamic program.
Preferred Qualifications
- Experience on machine learning accelerators, high-performance compute, or other large, high-bandwidth designs.
- Experience on a founding or early-stage silicon team, including standing up flows, methodology, or tooling from nothing.
- Experience with both partner-executed and fully in-house programs, and a view on the tradeoffs between them.
- Familiarity with the chip-package-system interface and the tradeoffs that cross it.
- Experience with hardware-software co-design and working directly with compiler, kernel, or runtime teams.
- Experience building or extending AI-assisted design, verification, or physical design flows.
- Depth in memory subsystems, on-die interconnect, numerics, or low-power design.
Representative Projects
- Writing the specification for a compute datapath and defending its numeric format strategy against the alternatives.
- Standing up front-end flows and release management from scratch, then handing releases to an ASIC partner on a fixed cadence.
- Running fast in-house place-and-route loops on a critical block and feeding PPA reality back into the architecture.
- Selecting and qualifying PHY IP, then validating it on first silicon.
- Building a formal verification methodology for a new block and deciding where formal earns its keep versus simulation.
- Defining test strategy and the automated-test-equipment handoff interface with our partner.
- Prototyping a AI-assisted workflow for RTL review, coverage triage, or specification consistency checking, and reporting honestly on what it did and did not do.
- Debugging a first-silicon failure that crosses your domain and someone else's.
Annual Salary
$320,000-$485,000 USD
We Offer
- Competitive compensation and benefits
- Optional equity donation matching
- Generous vacation and parental leave
- Flexible working hours
- Lovely office space in San Francisco
How We're Different
We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact - advancing our long-term goals of steerable, trustworthy AI - rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.
Come Work with Us!
Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.
Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links-visit anthropic.com/careers directly for confirmed position openings.
© Label Your Data. This job description was sourced from the employer's public career page. TheJob is not the employer — we index the posting and route candidates to the source. All content rights and hiring decisions belong to the employer.
Label Your Data provides secure and high quality data annotation services for Computer Vision or NLP applications since 2020. We help Data Scientists and AI Engineers streamline the dataset labeling and focus on model development.About Label Your Data:— Founded in 2020;— 200+ annotation experts in Europe, LATAM and Africa;— 98%+ annotation accuracy benchmark;— 55 supported languages;— PCI/DSS certified;— ISO/IEC 27001:2013 certified;— GDPR, CCPA and HIPAA-compliant;— HQs in North America, EU and Asia.Our experience spans over 20 industries including Automotive, Robotics, Agriculture, E-commerce, Retail, Healthcare, Manufacturing, Fintech and Insurance.Our core services include but are not limited to:— Image & video annotation: 2D boxes, OCR, object/action detection, polygons, key points, semantic segmentation, 3D cuboids;— Text annotation: classification, NER, intent & sentiment analysis, prompts creation, Q&A pairs generation;— Audio annotation: transcription, sentiment recognition;— Sensor data annotation;— Data classification & categorization;— Data entry;— Data collection;— Model validation.
More at Label Your Data
All 1589 roles
AI Platform Engineer, Infrastructure
Label Your Data · United States

AI Infrastructure Security Engineer
Label Your Data · United States

Product Manager
Label Your Data · United States

Machine Learning Engineer, Applied AI - Deployed
Label Your Data · United Arab Emirates