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Principal Engineer – Time-Series & Sensor Reasoning Models Careers at Analog Devices in San Jose, California | Apply Now

Analog Devices

Principal Engineer – Time-Series & Sensor Reasoning Models Careers at Analog Devices in San Jose, California | Apply Now

full-timePosted: Jan 29, 2026

Job Description

Principal Engineer – Time-Series & Sensor Reasoning Models Careers at Analog Devices in San Jose, California and Rio Robles, California | Join Lorenz Labs

Overview: Pioneering Physical Intelligence at Analog Devices Lorenz Labs

Imagine engineering AI that doesn't just process language or images, but truly understands the physical world through time, sensors, and dynamic signals. At Analog Devices in San Jose, California and Rio Robles, California, Lorenz Labs is creating the future of Physical Intelligence—foundation models that reason about audio waves, motion patterns, physiological signals, and environmental contexts with human-like intuition.

As a Principal Engineer – Time-Series & Sensor Reasoning Models, you'll lead the charge in developing next-generation architectures that unify multimodal sensor streams into coherent, context-aware reasoning systems. This isn't incremental AI research; it's building the Artificial Engineer—AI capable of simulating, understanding, and designing electro-physical systems.

Analog Devices (NASDAQ: ADI), with over $9 billion in FY24 revenue and 24,000 global employees, bridges the physical and digital worlds. Lorenz Labs, our advanced AI group within Edge AI, pushes beyond vision-language models into the temporal and sensory domains. Your work will power ADI's PhysGPT suite, transforming industries from digital healthcare and mobility to digitized factories and climate monitoring.

Based in the heart of Silicon Valley's innovation ecosystem in San Jose, California, and our advanced facilities in Rio Robles, California, you'll collaborate with world-class hardware engineers, signal processing experts, and AI researchers. This role demands 10% travel for conferences and partnerships, offering visibility at NeurIPS, ICLR, ICML, and ICASSP.

A Day in the Life of a Principal Engineer at Lorenz Labs

Your morning begins diving into the latest time-series foundation model training runs on our distributed AWS/GCP clusters. Reviewing metrics from Chronos-inspired architectures processing multi-sensor streams—IMU data fused with audio spectrograms and PPG signals—you identify breakthroughs in cross-modal alignment.

By mid-morning, you're in a co-design session with ADI's hardware teams, optimizing Tiny Recursive Models for edge deployment on resource-constrained MCUs. Lunch sparks ideas over causal inference techniques for anomaly detection in industrial vibration data.

Afternoons involve mentoring junior researchers on DPO alignment for physical reasoning tasks, followed by experimentation with Liquid Neural Networks that capture long-range temporal dependencies better than Transformers. Evenings might see you drafting a NeurIPS submission on sensor fusion frameworks that enable robots to interpret environments through dynamic acoustic cues.

This rhythm of research, collaboration, and innovation defines life at Lorenz Labs—where every day advances the frontier of physically-intelligent AI.

Why San Jose and Rio Robles, California? The Perfect Launchpad for AI Innovation

San Jose, California anchors Silicon Valley's epicenter, home to Stanford, Google, and countless AI pioneers. Our state-of-the-art labs immerse you in a talent-dense ecosystem where ideas cross-pollinate daily. From networking at ML meetups to recruiting top PhDs, San Jose fuels your career acceleration.

Rio Robles, California offers advanced manufacturing and testing facilities, bridging research to production-scale edge AI. Just minutes from San Jose, it provides the ideal balance of cutting-edge R&D and real-world deployment expertise.

California's innovation culture, combined with ADI's global reach, positions you at the intersection of academia, industry, and hardware reality. Enjoy year-round mild weather, world-class dining, and proximity to Yosemite and coastal escapes—while shaping AI that understands the physical world.

Career Growth: From Principal Engineer to AI Visionary

At Analog Devices, Principal Engineers don't plateau. Lorenz Labs offers clear paths to Distinguished Engineer, Director of AI Research, and VP of Physical Intelligence. Lead cross-functional teams building PhysGPT, publish groundbreaking papers, and patent novel architectures.

Access ADI University for executive leadership training, present at global conferences, and shape our Artificial Engineer roadmap. With 10+ years experience as baseline, you'll mentor the next generation while expanding your influence across ADI's $9B ecosystem.

Rewards: Compensation That Reflects Your Impact

Expected base salary spans $170,775–$256,163 USD, varying by experience and location within San Jose and Rio Robles, California. Performance bonuses, comprehensive medical/vision/dental, 401k matching, generous PTO, holidays, and sick time complete the package.

Equity grants align your success with ADI's growth. Unlimited conference travel budgets, cutting-edge compute resources, and global collaboration opportunities amplify your professional rewards.

Lorenz Labs Culture: Frontier Thinkers United by Mission

We attract curious minds obsessed with the physical-digital boundary. Flat hierarchies foster bold ideas; psychological safety encourages wild hypotheses about time-series reasoning. Weekly research shares, AI reading groups, and hardware hackathons build deep connections.

Diversity drives innovation—our teams span global backgrounds, united by passion for Physical Intelligence. 1st shift flexibility supports work-life balance in California's vibrant communities.

Apply Now: Shape the Future of Physical AI

U.S. Citizens, Permanent Residents, and protected individuals preferred due to export controls. Submit your CV showcasing time-series expertise, publications, and sensor fusion experience. Join us in San Jose or Rio Robles, California to build AI that reasons like physicists and engineers.

EEO Statement: Analog Devices celebrates diversity. We provide equal opportunity regardless of race, color, religion, age, ancestry, national origin, sex, sexual orientation, gender identity, disability, veteran status, or other protected characteristics.

Frequently Asked Questions

Locations

  • San Jose, California, United States
  • Rio Robles, California, United States

Salary

170,775 - 256,163 USD / yearly

Estimated Salary Rangehigh confidence

170,775 - 256,163 USD / yearly

Source: ai estimated

* This is an estimated range based on market data and may vary based on experience and qualifications.

Skills Required

  • Time-series machine learningintermediate
  • Signal processing expertiseintermediate
  • Foundation models (Chronos, TimesFM, TimeGPT)intermediate
  • Sensor modeling and fusionintermediate
  • PPG, IMU, audio, photonics sensorsintermediate
  • Context-aware multimodal reasoningintermediate
  • Audio perception and biosignalsintermediate
  • Representation learningintermediate
  • Causal inference in temporal dataintermediate
  • Motif discovery in high-dimensional dataintermediate
  • Model benchmarking and evaluationintermediate
  • LoRA, Q-LoRA, adapter-tuningintermediate
  • DPO (Direct Preference Optimization)intermediate
  • RLAIF (Reinforcement Learning from AI Feedback)intermediate
  • Python and PyTorch proficiencyintermediate
  • Large-scale training pipelinesintermediate
  • AWS, GCP distributed systemsintermediate
  • Hardware-software co-designintermediate
  • Edge AI deploymentintermediate
  • Recursive neural architecturesintermediate
  • Liquid Neural Networksintermediate
  • State-Space Transformersintermediate
  • Tiny Recursive Modelsintermediate
  • Sensor fusion frameworksintermediate
  • Anomaly detection in time-seriesintermediate
  • Forecasting modelsintermediate

Required Qualifications

  • Ph.D. in Electrical Engineering, Computer Science, or Applied Physics (experience)
  • 10+ years research and industrial experience in ML or signal processing (experience)
  • Deep expertise in time-series foundation models (experience)
  • Strong background in multi-sensor signal fusion (experience)
  • Experience with context-aware audio reasoning (experience)
  • Proficiency in multimodal sensor data integration (experience)
  • Hands-on with parameter-efficient fine-tuning (LoRA/Q-LoRA) (experience)
  • Proven track record in reward-based optimization (DPO, PPO) (experience)
  • Fluency in Python, PyTorch, and distributed training (experience)
  • Demonstrated leadership in AI hardware integration (experience)
  • Record of publications at NeurIPS, ICLR, ICML, ICASSP (experience)
  • Patents or open-source contributions in sensing AI (experience)
  • Experience bridging ML with embedded systems (experience)
  • Knowledge of edge inference optimization (experience)
  • Cross-disciplinary collaboration skills (experience)

Responsibilities

  • Lead R&D on multi-sensor time-series foundation models
  • Develop Tiny Recursive Models for edge deployment
  • Advance sensor fusion across audio, motion, photonic domains
  • Create audio reasoning models for context interpretation
  • Build benchmarking pipelines for temporal models
  • Apply LoRA, Q-LoRA, and adapter-tuning to sensor datasets
  • Implement DPO and RLAIF for physical reasoning tasks
  • Partner with hardware teams for energy-efficient designs
  • Publish research at top ML and signal-processing conferences
  • Mentor junior researchers in Lorenz Labs
  • Explore Liquid Neural Networks and State-Space Transformers
  • Enable anomaly detection and forecasting in industrial systems
  • Develop tools for physics-aligned model optimization
  • Co-design architectures for real-time sensing applications
  • Shape strategy for PhysGPT and Artificial Engineer vision
  • Integrate multimodal data for embodied AI systems
  • Optimize models for resource-constrained edge hardware

Benefits

  • general: Competitive salary $170,775 - $256,163 USD
  • general: Discretionary performance-based bonus
  • general: Comprehensive medical coverage
  • general: Vision and dental insurance
  • general: 401k retirement savings plan
  • general: Paid vacation time
  • general: Paid holidays
  • general: Paid sick time
  • general: Work at the frontier of Physical Intelligence
  • general: Access to ADI's global semiconductor ecosystem
  • general: Collaboration with world-class hardware engineers
  • general: Opportunities to publish at NeurIPS, ICLR, ICML
  • general: Mentorship and leadership development
  • general: 10% travel for conferences and partnerships
  • general: Cutting-edge AI research environment
  • general: Influence on PhysGPT foundation models
  • general: State-of-the-art computing resources

Target Your Resume for "Principal Engineer – Time-Series & Sensor Reasoning Models Careers at Analog Devices in San Jose, California | Apply Now" , Analog Devices

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Tags & Categories

Principal Engineer Analog DevicesTime-Series AI jobs San JoseSensor Reasoning Models CaliforniaLorenz Labs careersPhysical Intelligence AIFoundation models time-seriesEdge AI engineerPhysGPT Analog DevicesSensor fusion machine learningTiny Recursive Models jobsLiquid Neural NetworksState-Space Transformers AIMultimodal sensor AI San JoseAudio reasoning modelsDPO RLAIF specialistPyTorch time-series expertML signal processing CaliforniaArtificial Engineer AINeurIPS researcher jobsEdge inference optimizationAnomaly detection AIIndustrial IoT AI engineerBiosignals machine learningRio Robles AI careersArtificial IntelligenceMachine LearningSignal ProcessingEdge AISensor TechnologyTime-Series AnalysisResearch EngineeringSemiconductors

Answer 10 quick questions to check your fit for Principal Engineer – Time-Series & Sensor Reasoning Models Careers at Analog Devices in San Jose, California | Apply Now @ Analog Devices.

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Analog Devices logo

Principal Engineer – Time-Series & Sensor Reasoning Models Careers at Analog Devices in San Jose, California | Apply Now

Analog Devices

Principal Engineer – Time-Series & Sensor Reasoning Models Careers at Analog Devices in San Jose, California | Apply Now

full-timePosted: Jan 29, 2026

Job Description

Principal Engineer – Time-Series & Sensor Reasoning Models Careers at Analog Devices in San Jose, California and Rio Robles, California | Join Lorenz Labs

Overview: Pioneering Physical Intelligence at Analog Devices Lorenz Labs

Imagine engineering AI that doesn't just process language or images, but truly understands the physical world through time, sensors, and dynamic signals. At Analog Devices in San Jose, California and Rio Robles, California, Lorenz Labs is creating the future of Physical Intelligence—foundation models that reason about audio waves, motion patterns, physiological signals, and environmental contexts with human-like intuition.

As a Principal Engineer – Time-Series & Sensor Reasoning Models, you'll lead the charge in developing next-generation architectures that unify multimodal sensor streams into coherent, context-aware reasoning systems. This isn't incremental AI research; it's building the Artificial Engineer—AI capable of simulating, understanding, and designing electro-physical systems.

Analog Devices (NASDAQ: ADI), with over $9 billion in FY24 revenue and 24,000 global employees, bridges the physical and digital worlds. Lorenz Labs, our advanced AI group within Edge AI, pushes beyond vision-language models into the temporal and sensory domains. Your work will power ADI's PhysGPT suite, transforming industries from digital healthcare and mobility to digitized factories and climate monitoring.

Based in the heart of Silicon Valley's innovation ecosystem in San Jose, California, and our advanced facilities in Rio Robles, California, you'll collaborate with world-class hardware engineers, signal processing experts, and AI researchers. This role demands 10% travel for conferences and partnerships, offering visibility at NeurIPS, ICLR, ICML, and ICASSP.

A Day in the Life of a Principal Engineer at Lorenz Labs

Your morning begins diving into the latest time-series foundation model training runs on our distributed AWS/GCP clusters. Reviewing metrics from Chronos-inspired architectures processing multi-sensor streams—IMU data fused with audio spectrograms and PPG signals—you identify breakthroughs in cross-modal alignment.

By mid-morning, you're in a co-design session with ADI's hardware teams, optimizing Tiny Recursive Models for edge deployment on resource-constrained MCUs. Lunch sparks ideas over causal inference techniques for anomaly detection in industrial vibration data.

Afternoons involve mentoring junior researchers on DPO alignment for physical reasoning tasks, followed by experimentation with Liquid Neural Networks that capture long-range temporal dependencies better than Transformers. Evenings might see you drafting a NeurIPS submission on sensor fusion frameworks that enable robots to interpret environments through dynamic acoustic cues.

This rhythm of research, collaboration, and innovation defines life at Lorenz Labs—where every day advances the frontier of physically-intelligent AI.

Why San Jose and Rio Robles, California? The Perfect Launchpad for AI Innovation

San Jose, California anchors Silicon Valley's epicenter, home to Stanford, Google, and countless AI pioneers. Our state-of-the-art labs immerse you in a talent-dense ecosystem where ideas cross-pollinate daily. From networking at ML meetups to recruiting top PhDs, San Jose fuels your career acceleration.

Rio Robles, California offers advanced manufacturing and testing facilities, bridging research to production-scale edge AI. Just minutes from San Jose, it provides the ideal balance of cutting-edge R&D and real-world deployment expertise.

California's innovation culture, combined with ADI's global reach, positions you at the intersection of academia, industry, and hardware reality. Enjoy year-round mild weather, world-class dining, and proximity to Yosemite and coastal escapes—while shaping AI that understands the physical world.

Career Growth: From Principal Engineer to AI Visionary

At Analog Devices, Principal Engineers don't plateau. Lorenz Labs offers clear paths to Distinguished Engineer, Director of AI Research, and VP of Physical Intelligence. Lead cross-functional teams building PhysGPT, publish groundbreaking papers, and patent novel architectures.

Access ADI University for executive leadership training, present at global conferences, and shape our Artificial Engineer roadmap. With 10+ years experience as baseline, you'll mentor the next generation while expanding your influence across ADI's $9B ecosystem.

Rewards: Compensation That Reflects Your Impact

Expected base salary spans $170,775–$256,163 USD, varying by experience and location within San Jose and Rio Robles, California. Performance bonuses, comprehensive medical/vision/dental, 401k matching, generous PTO, holidays, and sick time complete the package.

Equity grants align your success with ADI's growth. Unlimited conference travel budgets, cutting-edge compute resources, and global collaboration opportunities amplify your professional rewards.

Lorenz Labs Culture: Frontier Thinkers United by Mission

We attract curious minds obsessed with the physical-digital boundary. Flat hierarchies foster bold ideas; psychological safety encourages wild hypotheses about time-series reasoning. Weekly research shares, AI reading groups, and hardware hackathons build deep connections.

Diversity drives innovation—our teams span global backgrounds, united by passion for Physical Intelligence. 1st shift flexibility supports work-life balance in California's vibrant communities.

Apply Now: Shape the Future of Physical AI

U.S. Citizens, Permanent Residents, and protected individuals preferred due to export controls. Submit your CV showcasing time-series expertise, publications, and sensor fusion experience. Join us in San Jose or Rio Robles, California to build AI that reasons like physicists and engineers.

EEO Statement: Analog Devices celebrates diversity. We provide equal opportunity regardless of race, color, religion, age, ancestry, national origin, sex, sexual orientation, gender identity, disability, veteran status, or other protected characteristics.

Frequently Asked Questions

Locations

  • San Jose, California, United States
  • Rio Robles, California, United States

Salary

170,775 - 256,163 USD / yearly

Estimated Salary Rangehigh confidence

170,775 - 256,163 USD / yearly

Source: ai estimated

* This is an estimated range based on market data and may vary based on experience and qualifications.

Skills Required

  • Time-series machine learningintermediate
  • Signal processing expertiseintermediate
  • Foundation models (Chronos, TimesFM, TimeGPT)intermediate
  • Sensor modeling and fusionintermediate
  • PPG, IMU, audio, photonics sensorsintermediate
  • Context-aware multimodal reasoningintermediate
  • Audio perception and biosignalsintermediate
  • Representation learningintermediate
  • Causal inference in temporal dataintermediate
  • Motif discovery in high-dimensional dataintermediate
  • Model benchmarking and evaluationintermediate
  • LoRA, Q-LoRA, adapter-tuningintermediate
  • DPO (Direct Preference Optimization)intermediate
  • RLAIF (Reinforcement Learning from AI Feedback)intermediate
  • Python and PyTorch proficiencyintermediate
  • Large-scale training pipelinesintermediate
  • AWS, GCP distributed systemsintermediate
  • Hardware-software co-designintermediate
  • Edge AI deploymentintermediate
  • Recursive neural architecturesintermediate
  • Liquid Neural Networksintermediate
  • State-Space Transformersintermediate
  • Tiny Recursive Modelsintermediate
  • Sensor fusion frameworksintermediate
  • Anomaly detection in time-seriesintermediate
  • Forecasting modelsintermediate

Required Qualifications

  • Ph.D. in Electrical Engineering, Computer Science, or Applied Physics (experience)
  • 10+ years research and industrial experience in ML or signal processing (experience)
  • Deep expertise in time-series foundation models (experience)
  • Strong background in multi-sensor signal fusion (experience)
  • Experience with context-aware audio reasoning (experience)
  • Proficiency in multimodal sensor data integration (experience)
  • Hands-on with parameter-efficient fine-tuning (LoRA/Q-LoRA) (experience)
  • Proven track record in reward-based optimization (DPO, PPO) (experience)
  • Fluency in Python, PyTorch, and distributed training (experience)
  • Demonstrated leadership in AI hardware integration (experience)
  • Record of publications at NeurIPS, ICLR, ICML, ICASSP (experience)
  • Patents or open-source contributions in sensing AI (experience)
  • Experience bridging ML with embedded systems (experience)
  • Knowledge of edge inference optimization (experience)
  • Cross-disciplinary collaboration skills (experience)

Responsibilities

  • Lead R&D on multi-sensor time-series foundation models
  • Develop Tiny Recursive Models for edge deployment
  • Advance sensor fusion across audio, motion, photonic domains
  • Create audio reasoning models for context interpretation
  • Build benchmarking pipelines for temporal models
  • Apply LoRA, Q-LoRA, and adapter-tuning to sensor datasets
  • Implement DPO and RLAIF for physical reasoning tasks
  • Partner with hardware teams for energy-efficient designs
  • Publish research at top ML and signal-processing conferences
  • Mentor junior researchers in Lorenz Labs
  • Explore Liquid Neural Networks and State-Space Transformers
  • Enable anomaly detection and forecasting in industrial systems
  • Develop tools for physics-aligned model optimization
  • Co-design architectures for real-time sensing applications
  • Shape strategy for PhysGPT and Artificial Engineer vision
  • Integrate multimodal data for embodied AI systems
  • Optimize models for resource-constrained edge hardware

Benefits

  • general: Competitive salary $170,775 - $256,163 USD
  • general: Discretionary performance-based bonus
  • general: Comprehensive medical coverage
  • general: Vision and dental insurance
  • general: 401k retirement savings plan
  • general: Paid vacation time
  • general: Paid holidays
  • general: Paid sick time
  • general: Work at the frontier of Physical Intelligence
  • general: Access to ADI's global semiconductor ecosystem
  • general: Collaboration with world-class hardware engineers
  • general: Opportunities to publish at NeurIPS, ICLR, ICML
  • general: Mentorship and leadership development
  • general: 10% travel for conferences and partnerships
  • general: Cutting-edge AI research environment
  • general: Influence on PhysGPT foundation models
  • general: State-of-the-art computing resources

Target Your Resume for "Principal Engineer – Time-Series & Sensor Reasoning Models Careers at Analog Devices in San Jose, California | Apply Now" , Analog Devices

Get personalized recommendations to optimize your resume specifically for Principal Engineer – Time-Series & Sensor Reasoning Models Careers at Analog Devices in San Jose, California | Apply Now. Takes only 15 seconds!

AI-powered keyword optimization
Skills matching & gap analysis
Experience alignment suggestions

Check Your ATS Score for "Principal Engineer – Time-Series & Sensor Reasoning Models Careers at Analog Devices in San Jose, California | Apply Now" , Analog Devices

Find out how well your resume matches this job's requirements. Get comprehensive analysis including ATS compatibility, keyword matching, skill gaps, and personalized recommendations.

ATS compatibility check
Keyword optimization analysis
Skill matching & gap identification
Format & readability score

Tags & Categories

Principal Engineer Analog DevicesTime-Series AI jobs San JoseSensor Reasoning Models CaliforniaLorenz Labs careersPhysical Intelligence AIFoundation models time-seriesEdge AI engineerPhysGPT Analog DevicesSensor fusion machine learningTiny Recursive Models jobsLiquid Neural NetworksState-Space Transformers AIMultimodal sensor AI San JoseAudio reasoning modelsDPO RLAIF specialistPyTorch time-series expertML signal processing CaliforniaArtificial Engineer AINeurIPS researcher jobsEdge inference optimizationAnomaly detection AIIndustrial IoT AI engineerBiosignals machine learningRio Robles AI careersArtificial IntelligenceMachine LearningSignal ProcessingEdge AISensor TechnologyTime-Series AnalysisResearch EngineeringSemiconductors

Answer 10 quick questions to check your fit for Principal Engineer – Time-Series & Sensor Reasoning Models Careers at Analog Devices in San Jose, California | Apply Now @ Analog Devices.

Quiz Challenge
10 Questions
~2 Minutes
Instant Score

Related Books and Jobs

No related jobs found at the moment.