Principal AI/ML Engineer, Time-Series & Sensor Reasoning Models (Lorenz Labs)

Job Title

Principal AI/ML Engineer, Time-Series & Sensor Reasoning Models (Lorenz Labs)

Role Summary

Senior engineering role to research and develop foundation-scale time-series and multimodal sensor reasoning models that bridge physics-aware sensing and large-scale temporal AI. You will design architectures for cross-sensor representation, alignment, and deployable edge intelligence in domains such as automotive, health, industrial systems, and robotics.

This role partners with hardware, signal-processing, and systems teams to convert research into energy-efficient, real-time sensing solutions and represents the team at major ML and signal-processing venues.

Experience Level

Senior - requires substantial senior experience. The posting specifies 10+ years of experience developing AI/ML products.

Responsibilities

Lead research and engineering to create deployable time-series foundation models and agentic solutions for multimodal sensor data.

• Lead R&D on time-series agents for edge devices combining anomaly detection, forecasting, and reasoning across multiple sensor modalities (electrical, audio, motion, physiological, etc.).
• Design models that incorporate additional context modalities such as text and images for cross-modal reasoning.
• Advance sensor fusion and cross-modal alignment across electrical, acoustic, inertial, and photonic domains.
• Build benchmarking pipelines for representation robustness, interpretability, and hardware performance.
• Apply parameter-efficient fine-tuning and alignment methods (LoRA, Q-LoRA, adapter-tuning, contrastive alignment).
• Investigate reinforcement and reward-based alignment techniques (DPO, RLAIF, PPO) for sensory reasoning tasks.
• Collaborate with hardware, signal-processing, and systems teams to co-design real-time, energy-efficient architectures.
• Design statistical experiments and data collection protocols for subject-matter experts to generate training datasets.
• Publish and present results at major conferences (NeurIPS, ICLR, ICML, ICASSP, KDD) and mentor junior researchers.
• Travel as needed - up to approximately 10% of the time.

Requirements

Must-have technical skills and experience required to perform the role; preferred items are noted separately.

• 10+ years developing AI/ML products, with demonstrable applied results.
• Deep expertise in time-series ML, signal processing, and time-series foundation models, with hands-on experience training or fine-tuning such models.
• Proficiency in representation learning, time-series encoding, compression, and motif discovery for high-dimensional temporal data.
• Knowledge of state-of-the-art time-series reasoning models (cross-attention, multimodal embedding), time-series agentic systems, memory mechanisms, and retrieval-augmented generation for temporal data.
• Experience with parameter-efficient fine-tuning and reward-based optimization methods (LoRA/Q-LoRA, DPO, PPO, RLAIF).
• Strong skills in statistical hypothesis testing, experimental design, and causal discovery.
• Fluency in Python and PyTorch and experience with large-scale training pipelines on cloud or distributed systems (AWS, GCP, or equivalent).
• Ability to collaborate across ML, hardware, and embedded systems and to translate research prototypes into deployable systems.
• Nice-to-have: leadership experience combining technical solutions with business needs for embedded systems; record of patents, publications, or open-source contributions.

Education Requirements

Preferred: Ph.D. in Electrical Engineering, Computer Science, or Applied Physics. (No other degree requirements or equivalents explicitly specified in the posting.)

About the Company

Company: Analog Devices

Headquarters: Norwood, Massachusetts, USA

Analog Devices is a leading global semiconductor company that bridges the physical and digital worlds, enabling breakthroughs at the Intelligent Edge. With a focus on innovation, ADI develops solutions that drive advancements in digitized factories, mobility, and digital healthcare. The company employs around 24,000 people globally and reported revenues exceeding $9 billion in FY24, creating technologies that transform lives across various sectors.