Manufacturing Engineer - Data Center Hardware

As a Manufacturing Engineer within the Data Center Infrastructure organization, you will own how Anthropic’s servers, racks, and accelerator systems are built at our contract manufacturing and ODM partners. You will design and qualify the assembly, integration, and test processes for each product, bring up new lines and new sites, and drive yield, cycle time, and manufacturing cost once a product is in production. As a subject matter expert in electronics and rack-level manufacturing, you will give the design team early manufacturability feedback, set the process standards our partners build to, and be on the floor when a line is coming up or a yield problem needs solving. If you have built manufacturing processes for complex hardware at a CM or ODM, are passionate about HPC data centers, & enjoy working in complex, fast-paced environments, we welcome you to apply.

This is a hands-on role with up to 50% travel to partner factories in the US and abroad. You should be as comfortable addressing issues on the line as you are presenting a vendor improvement plan to leadership., * Design and document the assembly, rack integration, and test process for new server and rack products, including work instructions, process flows, takt and cycle time targets, and line layout.

• Lead new line and new site bring-up at CM/ODM partners, from process validation and capacity verification through pilot builds and release to mass production.
• Specify, source, and validate tooling, fixtures, and test equipment.
• Own first-pass yield, cycle time, and process capability in production; run SPC, analyze failure and rework data, and drive corrective actions with manufacturing partners.
• Provide design-for-manufacturing and design-for-test feedback during product development and represent manufacturing in pilot build reviews.
• Qualify process changes and engineering changes on the line, including PFMEA updates, control plan revisions, and operator training, before changes are cut in.
• Replicate a qualified process from one line or site to another without a yield or throughput regression, and audit partner lines against Anthropic standards.
• Partner with product engineering, test engineering, quality, and supply chain to resolve systemic build issues and reduce per unit cost.

• Have 8+ years of experience in manufacturing engineering or process engineering for complex electromechanical or electronics products built at a contract manufacturer or ODM.
• Have designed and released a production process end to end, including line layout, work instructions, fixtures, and test, and owned its yield and cycle time in mass production.
• Have led a new line or site bring-up at a manufacturing partner.
• Are experienced with common manufacturing engineering tools such as: PFMEA, control plans, SPC, process capability, gauge R&R, DFM/DFT, and structured root cause methods such as 8D.
• Are comfortable on the factory floor and can diagnose a process problem through observation and analysis of factory telemetry.
• Communicate clearly with partner engineers and operators on the floor and with leadership in a readout.
• Can travel to partner manufacturing sites, domestic and international up to 50% of the time.
• Have a degree in Mechanical, Industrial, Manufacturing, or Electrical Engineering, or equivalent practical experience., * Experience manufacturing servers, racks, switches, or accelerator systems at data center scale.
• Experience with liquid-cooled rack integration, including cold plates, manifolds, CDUs, and leak and fill test processes.
• Experience with SMT and PCBA process, box build, and rack-level system integration and test.
• Experience qualifying a second CM or second site for an existing product.
• Experience with lean and continuous improvement methods (value stream mapping, kaizen, Six Sigma) applied at a manufacturing partner.
• A Master’s degree or better in a relevant engineering discipline., 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.

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. Annual Salary: $320,000-$405,000 USD, 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. Guidance on Candidates’ AI Usage: Learn about our policy for using AI in our application process.

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., 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.

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 Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.