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Bose

Premium audio hardware maker with psychoacoustics

Principal Research Architect

AI & Machine LearningConfirmed live in the last 24 hours
Full-timeFramingham, MA, USA

About the Job

Requirements

  • A bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, Systems Engineering, Robotics, or a related technical discipline is required.
  • At least 10 years of experience designing, architecting, and delivering complex software or systems solutions is required.
  • Experience architecting connected-device, embedded, distributed, Internet of Things, robotics, or edge-computing systems is required, including hands-on integration and evaluation of machine-learning models and understanding how model architecture affects system behavior.
  • Hands-on software development and prototyping experience is required, including the ability to build, debug, and evaluate experimental systems.
  • Practical experience developing software on Linux-based and/or embedded platforms is required.
  • A deep understanding of networking, application programming interfaces, messaging systems, event-driven architectures, and software integration patterns is required.
  • Experience debugging and measuring behavior across hardware, software, and communication boundaries is required.
  • Practical understanding of machine-learning processing pipelines, including input preparation, representations, and inference, sufficient to discuss trade-offs with model developers is required.
  • The candidate must be able to compare implementations, interpret measurements, and revise architectural decisions based on evidence.
  • Strong technical communication and collaboration skills, curiosity, and initiative as requirements evolve through experiments are required.
  • Experience designing or integrating audio or multimedia systems, including understanding streaming pipelines, timing, synchronization, and latency, is required.

Responsibilities

  • Design, implement, and compare software and system architectures through working prototypes and repeatable experiments.
  • Translate research questions into experiment specifications, baseline comparisons, measurable evaluation criteria, and failure tests.
  • Write and debug critical software components while working directly with devices, sensors, and compute platforms.
  • Define and test application programming interfaces, data models, messaging approaches, and interfaces across hardware, models, and software services.
  • Collaborate with Research teams to integrate machine-learning models and signal-processing capabilities into working systems.
  • Evaluate how model inputs, representations, and inference requirements affect quality, latency, memory, compute, power, and reliability, and provide actionable feedback to model developers.
  • Compare processing placement, communication, and coordination approaches, including behavior when connectivity or components fail.
  • Define synchronization, instrumentation, and reproducibility requirements with the engineers implementing experiments.
  • Evaluate third-party technologies against internal or open alternatives, considering technical fit, integration effort, portability, and maintenance.
  • Work with security, privacy, and platform specialists on trust boundaries, data access, and appropriate handling of sensor data.
  • Document evidence, architectural decisions, and unresolved questions.
  • Mentor engineers while remaining actively involved in implementation.

Desired Qualifications

  • Prior experience developing or training machine-learning models, providing practical insight into model-design trade-offs.
  • Experience deploying or optimizing inference on resource-constrained hardware.
  • Experience with MQTT, ROS 2, Bluetooth/BLE, device discovery, or comparable communication frameworks.
  • Background in robotics, connected products, wearables, automotive systems, industrial automation, sensing, or audio.
  • Experience experimenting with agentic development tools or building agent workflows, with an understanding of tool integration, execution boundaries, testing, and human oversight.
  • Experience guiding research or advanced-development work and turning experimental findings into reusable engineering approaches.
  • Experience with Python or comparable tools used in machine-learning and systems research.

About the Company

Bose

Premium audio hardware maker with psychoacoustics

Bose makes premium audio products and technologies for consumers, automotive makers, and professional installations. Its products use psychoacoustics to match how people perceive sound, with examples like noise-canceling headphones and spatial audio technologies such as TrueSpace. It differentiates itself through deep R&D, a long-term ownership structure that supports sustained investment, and a diversified model that includes direct-to-consumer sales, licensing, OEM automotive partnerships, and professional installations. Its goal is to deliver sound as it is meant to be heard and to grow its leadership in audio technology across premium consumer, automotive, and professional markets.

Company size
5,001-10,000
Company stage
Seed
Total funding
$430K
Headquarters
Framingham, MA
Founded
1964

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