About Careertakes

👉 Important disclosure: Careertakes is a third-party recruiting platform supporting this hiring process. If selected, you will be employed directly by our client, IT.

Applicants for this role may also receive access to additional matched opportunities through the Careertakes platform.

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What You’ll Do

Confidential client’s Client AI Architecture team is seeking a Deep Learning Hardware Engineer to help design and optimize next‑generation Neural Processing Unit (NPU) and AI accelerator technology for client/edge platforms. You will work at the intersection of AI, computer architecture, and hardware‑software co‑design to enable high‑performance, power‑efficient ML inference and foundational-model workloads.

• Contribute to the architecture and microarchitecture of neural compute engines and AI accelerators.
• Develop, simulate, and evaluate RTL (SystemVerilog/Verilog) implementations for ML‑focused hardware features.
• Profile and analyze AI models and workloads to identify performance, power, and efficiency opportunities.
• Define mapping strategies for neural networks onto accelerator primitives to improve throughput and latency.
• Apply and evaluate model optimization techniques (quantization, pruning, compression, sparsity) for efficient inference.
• Collaborate with architecture, compiler, software, and ML teams to co‑design hardware and software stacks.
• Use computer architecture principles (pipelining, parallelism, memory hierarchy, data movement) to guide design choices.
• Participate in technical innovation activities, including invention disclosures, patents, and publications.

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Qualifications

Minimum qualifications (required to be considered):

• Bachelor’s degree in Computer Science, Electrical Engineering, or a STEM field with 3+ years of relevant experience; OR Master’s degree with 2+ years; OR PhD with relevant coursework or experience.
• Hands‑on experience with digital logic and RTL design using SystemVerilog or Verilog.
• Practical knowledge of neural network model architectures, layers, activation functions, and modern topologies.
• Experience with Git workflows and repositories.
• Demonstrated work optimizing AI models for inference (quantization, pruning, compression).

Preferred qualifications:

• Familiarity with AI frameworks, neural computing ops, and hardware‑accelerated inference techniques.
• Experience deploying or optimizing models on NPUs, GPUs, or AI accelerators.
• Strong understanding of computer architecture concepts (multi‑core, caching, memory hierarchies, fixed‑point vs floating‑point).
• Experience collaborating across hardware, compiler, and ML research teams.

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Why Join

This role offers the chance to work on cutting‑edge AI and machine learning acceleration for client and edge devices, learn from experienced hardware and AI engineers, and influence next‑generation silicon and system designs. Confidential client offers competitive total compensation, benefits, and professional growth opportunities.

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Compensation & Work Model

• Annual pay range (for US locations): $149,750 — $240,710 USD.
• Work model: Hybrid (split time on‑site and off‑site) — specific schedule determined by the client.
• Benefits: competitive pay, stock or bonus opportunities, health, retirement, and paid time off programs (details subject to confidential client policies).

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Location & Employment Type

• Primary location: Orenco, OR, US.
• Employment type: Full‑time (College Grad / Professional level).
• This role may require on‑site days; final work model and location details are set by the confidential client.

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Legal & Recruitment Notes

• Confidential client does not charge fees during the hiring process. Report any request for payment.
• Immigration/sponsorship: subject to confidential client policy (candidates should ask their recruiter for details).
• Posting details (work model, location, time type) may change.

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Equal Opportunity & Hiring Transparency

Careertakes and our client are Equal Opportunity Employers committed to building a diverse and inclusive workforce. We prohibit discrimination or harassment of any kind. To support a fair and efficient hiring process, AI tools may be used to assist with application review or resume screening. These tools do not replace human decision-making. Final hiring decisions are made by people.

If you have questions about how your data is used, please contact us directly.