Product Engineer - Manufacturing Operations

5 дн. назад

USASeniorRemote

manufacturingyield analysisengineering changesroot cause analysistest debugging

Technical owner of hardware product manufacturing, ensuring quality from development through mass production with factory partnerships.

Обязанности

is building its own servers, racks, and accelerator systems with contract manufacturers and ODM partners, and deploying them across our fleet of data centers. We are seeking experienced engineers to own how well that hardware gets built.
As a Product Engineer on the Manufacturing Operations team, you are the technical owner of a product at the factory. During development, you gather manufacturing, test, and yield concerns, get them fixed in the design before each build, and sign off that the product is ready to move to the next stage. Once a product is in mass production, you keep it healthy by delivering engineering changes with minimal disruption, qualifying new components and second-source manufacturers, and root-causing yield and field failures.
This is a hands-on role with up to 50% travel to partner factories in the US and abroad. You should be as comfortable debugging a test failure on the line as you are presenting a corrective action plan to leadership.

Другое

’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.
Take a new accelerator rack from early evaluation to mass production at an ODM: audit the assembly and test process, set yield targets, confirm test coverage, and approve the transition.
Scale manufacturing from one line to multiple and then to a second site or second manufacturer without yield or throughput regressions.
Run a cross-functional root cause on field failures traced to a manufacturing gap, drive corrective action with the ODM/CM, and close the loop with the design itself when required.
Lead an engineering change across manufacturers: BOM and PLM updates, cut-in planning, partner training, validation, and monitor field failures/RMA.
Bring manufacturing requirements and validation data into each development phase review so the engineering team has a single prioritized list of what to fix before the next build.
Have carried a hardware product from early builds through mass production at a contract manufacturer or ODM.
Have set up or improved assembly and test processes at a manufacturing partner and drove yield, quality, and schedule commitments.
Use structured manufacturing and root-cause methods (DFM, FMEA, SPC, 8D or similar) as a matter of habit, and are an expert at translating messy failure data into clear decisions.
Can write a product-specific test plan and judge whether test coverage is sufficient.
Communicate clearly with partner engineers and operations staff on the floor as well as with leadership in a readout.
Are willing to travel to partner sites up to 50% of the time.
Have a degree in Electrical, Mechanical, Industrial, or Materials Engineering, or equivalent practical experience.
Have been the technical lead for a data center hardware program such as: server, storage, switch, rack, or accelerator.
Have stood up a new manufacturing line or site, or brought up a second CM for an existing product.
Have experience with liquid-cooled or high-power-density rack systems.
Possess a Master's degree in a relevant engineering discipline.
Have worked closely with sourcing and supply chain teams on component qualification and multi-sourcing strategies.
The annual compensation range for this role is listed below. 
For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.
Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience
Required field of study:  A field relevant to the role as demonstrated through coursework, training, or professional experience
Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position
Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
Visa sponsorship:  We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that recruiters only contact you
We believe that the highest-impact AI research will be big science. At 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.
The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to , including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
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. Guidance on Candidates' AI Usage:  Learn about  our policy for using AI in our application process.