Principal Engineer – Time-Series & Sensor Reasoning Models (Lorenz Labs)

What You'll Do

• Lead R&D on time-series foundation models that integrate multi-sensor streams (e.g., audio, motion, environmental, and physiological).
• Develop compact, recursive, and hybrid modeling approaches (e.g., Tiny Recursive Models, Liquid Neural Networks, State-Space Transformers) for efficient deployment on edge hardware.
• Advance research in sensor fusion, enabling cross-modal alignment between acoustic, inertial, and photonic domains.
• Explore audio reasoning models that interpret context and intent through dynamic acoustic and environmental cues.
• Create benchmarking pipelines for cross-domain time-series foundation models, covering representation robustness, interpretability, and hardware performance metrics.
• Apply alignment and fine-tuning methods such as LoRA, Q-LoRA, adapter-tuning, and contrastive alignment for multimodal sensor datasets.
• Investigate modern foundation alignment techniques, including DPO (Direct Preference Optimization) and RLAIF (Reinforcement Learning from AI Feedback) for physical and sensory reasoning tasks.
• Partner with ADI’s hardware, signal processing, and systems teams to co-design architectures for real-time, energy-efficient sensing applications.
• Publish and represent ADI at major ML and signal-processing venues (NeurIPS, ICLR, ICML, ICASSP, KDD), often in conjunction with leading AI industry partners.
• Mentor junior researchers and help shape Lorenz Labs’ strategy for foundation models that understand and reason about physical systems.
• Must Have Skills Deep expertise in time-series ML, signal processing, and foundation models (Chronos, TimesFM, TimeGPT, etc.).
• Strong background in sensor modeling and signal fusion (e.g., PPG, IMU, audio, photonics, or industrial sensors).
• Experience in context-aware and multimodal reasoning—especially involving audio perception, biosignals, or environmental context.
• Proficiency in representation learning, causal inference, and motif discovery in high-dimensional temporal data.
• Familiarity with benchmarking, evaluation, and robustness testing of foundation and fine-tuned models.
• Proven hands-on expertise with modern alignment and fine-tuning strategies, including parameter-efficient fine-tuning, LoRA/Q-LoRA, and reward-based optimization methods (DPO, PPO, RLAIF).
• Fluency in Python, PyTorch, and large-scale training pipelines using cloud or distributed systems (AWS, GCP, etc.).
• Ability to collaborate across disciplines—ML, hardware, and embedded systems—and translate research into deployable physical intelligence systems.
• Preferred Education and Experience Ph.D. in Electrical Engineering, Computer Science, or Applied Physics. 10+ years of combined research and industrial experience in ML, signal processing, or embedded sensing.
• Demonstrated leadership in bridging sensing hardware with foundation model architectures.
• Record of innovation through patents, publications, or open-source contributions.
• Why You Will Love Working Here At Lorenz Labs, you will work at the frontier of AI, sensors, and the physical world.
• You will help define a new paradigm—models that understand time, context, and matter—driving the next wave of physical intelligence.
• Backed by ADI’s data, hardware ecosystem, and scientific reach, you will shape the future of PhysGPT and the Artificial Engineer—where the edge learns to reason.
• For positions requiring access to technical data, Analog Devices, Inc. may have to obtain export licensing approval from the U.S.
• Department of Commerce - Bureau of Industry and Security and/or the U.S.
• Department of State - Directorate of Defense Trade Controls.
• As such, applicants for this position – except US Citizens, US Permanent Residents, and protected individuals as defined by 8 U.S.C. 1324b(a)(3) – may have to go through an export licensing review process.
• We foster a culture where everyone has an opportunity to succeed regardless of their race, color, religion, age, ancestry, national origin, social or ethnic origin, sex, sexual orientation, gender, gender identity, gender expression, marital status, pregnancy, parental status, disability, medical condition, genetic information, military or veteran status, union membership, and political affiliation, or any other legally protected group.
• EEO is the Law: Notice of Applicant Rights Under the Law .
• Job Req Type: Experienced Required Travel: Yes, 10% of the time Shift Type: 1st Shift/Days The expected wage range for a new hire into this position is $170,775 to $256,163.
• Actual wage offered may vary depending on work location , experience, education, training, external market data, internal pay equity, or other bona fide factors.
• This position qualifies for a discretionary performance-based bonus which is based on personal and company factors.
• This position includes medical, vision and dental coverage, 401k, paid vacation, holidays, and sick time , and other benefits.