Top AI & Machine Learning Jobs

Reposted 8 Days AgoSaved
Hybrid
Framingham, MA, USA
271K-373K Annually
Senior level
271K-373K Annually
Senior level
Automotive • eCommerce • Hardware • Music • Retail • Software • Wearables
Senior technical leader defining 10-year scientific visions and systems architecture for Bose Research franchises. Ensures coherence across AI/ML, sensing, signal processing, and edge domains; guides foundational IP, models, datasets, and evaluation frameworks. Oversees program architecture, technical governance, and translation of research into scalable platforms and products while representing Bose externally and collaborating with research and engineering stakeholders.
Top Skills: AcousticsAi/MlDatasetsDistributed SystemsEdge ComputingEvaluation FrameworksHuman-Centered Systems DesignMachine LearningModelsSensing SystemsSignal Processing
9 Days AgoSaved
Hybrid
Framingham, MA, USA
168K-231K Annually
Expert/Leader
168K-231K Annually
Expert/Leader
Automotive • eCommerce • Hardware • Music • Retail • Software • Wearables
Architect complex embedded hardware and software systems for next-generation audio products. Evaluate feasibility, tradeoffs, scalability, and system constraints across power, compute, memory, latency, performance, and security. Develop simulations, prototypes, AI agents, and automated engineering workflows for architecture exploration and verification. Translate audio, sensing, machine learning, and AI technologies into reusable platforms, frameworks, algorithms, and IP while providing principal-level technical leadership across engineering teams, suppliers, and partners.
Top Skills: Agentic WorkflowsAi AgentsDigital Audio Signal ProcessingDspsEdge AiEmbedded HardwareEmbedded SoftwareEmbedded SystemsHardware AccelerationLinuxMachine LearningNpusReal-Time SystemsSdksSimulationSocsTinyml
9 Days AgoSaved
Hybrid
Framingham, MA, USA
141K-194K Annually
Entry level
141K-194K Annually
Entry level
Automotive • eCommerce • Hardware • Music • Retail • Software • Wearables
Develop, optimize, and deploy audio and multimodal machine learning models on embedded and edge devices. Build real-time inference pipelines, convert models to efficient C/C++ implementations, and optimize latency, memory, SRAM, and power across MCUs, DSPs, NPUs, and accelerators. Collaborate with researchers, DSP experts, firmware engineers, and hardware teams to deliver production-ready embedded AI systems using model development, quantization, profiling, and on-device runtimes.
Top Skills: CC++CmakeDspExecutorchFreertosGlowMcuMlirNpuPythonTflite MicroTinyml
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