Staff Engineer, AI/ML Software

Analog DevicesBoston, MA
1d

About The Position

Join us at Analog Devices as a Staff AI/ML Software Engineer and lead the development of cutting-edge AI/ML systems that power real-time applications across industries like industrial automation, data centers, communications, and hardware design. At Analog Devices, we’re committed to pushing the boundaries of innovation in Physical AI. Be at its forefront, working at the intersection of hardware and software to deliver scalable, production-grade solutions. This role offers the opportunity to drive technical strategy, mentor teams, and shape the future of AI/ML systems.

Requirements

  • Expertise in time-series data processing (e.g., feature extraction, quality assessment).
  • Proficiency with hardware modeling tools (e.g., SPICE, Verilog, MATLAB).
  • Strong background in signal processing, control systems, or physics-based data analysis.
  • Experience with real-time or streaming data processing under performance constraints.
  • Proven ability to design scalable, high-performance ML systems and apply advanced ML algorithms.
  • Excellent communication skills to translate complex technical results into actionable insights.

Nice To Haves

  • Master’s or PhD in Electrical Engineering, Physics, Computer Science, or a related field with expertise in statistical signal processing, mixed signal design, or power electronics.
  • 8+ years of experience in hardware-related industries and/or machine learning engineering.

Responsibilities

  • Analyze and optimize time-series sensor data to ensure real-time performance.
  • Architect and deliver scalable AI/ML systems and reference designs for real-time applications.
  • Build proof-of-concepts (PoCs) and pilot systems, optimizing models for latency, throughput, cost, and power efficiency.
  • Develop surrogate models for large-scale device/system simulations.
  • Explore innovative agentic AI approaches for system optimization and planning.
  • Mentor engineers, establish best practices, and contribute to the AI/ML community through workshops and publications.
  • Contribute to HW deployment, configuration, and operational tooling.
  • Partition workloads on edge device architecture.
  • Collaborate with Solutions Engineers to assess data assets and deployment requirements.

Benefits

  • medical
  • vision
  • dental coverage
  • 401k
  • paid vacation
  • holidays
  • sick time
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