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Neuralink

Signal Processing Engineer

Austin, Texas, United States; South San Francisco, California, United StatesmidAdded 1 month ago

About this role

Neuralink is looking for a Signal Processing Engineer to create and enhance advanced digital signal processing algorithms for embedded systems. This role involves collaborating with various teams to deliver efficient algorithms that meet real-time processing requirements.

What you'll do

  • Develop signal processing algorithms for neural activity monitoring.
  • Create numerical algorithms for data compression to boost radio throughput.
  • Optimize algorithms for hardware constraints.
  • Verify algorithms and transition them to hardware-friendly formats.
  • Analyze accuracy, power, and resource trade-offs for SoCs.
  • Collaborate on custom on-chip processing pipeline architecture.

What they're looking for

  • BS, MS, or PhD in relevant field
  • 3+ years in DSP algorithm development
  • Strong numerical analysis skills
  • Understanding of fixed-point arithmetic
  • Proficiency in Python and C
  • Experience with Verilog/VHDL preferred
  • Background in optimizing for power/area/latency
  • Familiarity with dedicated DSP cores

Benefits

  • Opportunity to impact the world positively
  • Growth potential with rapid advancement
  • Medical, dental, and vision insurance
  • Paid holidays
  • Commuter benefits
  • Meals provided
  • Equity compensation (RSUs)
  • 401(k) plan
  • Parental leave
  • Flexible time off
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Neuralink

Neuralink develops brain-computer interface technology and neurosurgical robots to enable direct interaction between the brain and computing systems. The company is hiring engineers across clinical implementation, user interface design, manufacturing, and software development to support its pioneering medical devices and surgical systems.

View all jobs at Neuralink

Likely interview questions

  • Walk us through your experience developing digital signal processing algorithms for embedded or hardware-constrained systems. What were the key challenges you faced?
  • Describe a time when you had to optimize an algorithm for fixed-point arithmetic or quantization. How did you balance accuracy, latency, and power consumption?