Staff AI/ML Engineer, Time-Series & Sensor Reasoning Models

About the role

Analog Devices is seeking a Staff AI/ML Engineer to build time-series and sensor foundation models for its Lorenz Labs team. The role develops architectures that unify multimodal sensor data (electrical, audio, motion, photonic and physiological signals) into a foundation for context-aware reasoning across time, contributing to the Faraday suite of physically-intelligent reasoning models. It works on multi-modal time series models using state-of-the-art techniques in time series embeddings, cross-attention, reinforcement learning and time series agentic solutions.

Key responsibilities

• Lead R&D on intelligent time-series agents for the edge, combining anomaly detection, reasoning and forecasting foundation models that also use text and image as additional context.
• Advance sensor fusion research and create benchmarking pipelines for cross-domain time-series models covering robustness, interpretability and hardware performance.
• Apply LoRA, Q-LoRA, adapter tuning and contrastive alignment, and investigate DPO and RLAIF for physical and sensory reasoning tasks.
• Co-design architectures with hardware, signal processing and systems teams for real-time, energy-efficient sensing applications.
• Design statistical experiments to collect sensor data and mentor junior researchers.

Required profile

• 6+ years of experience developing software products with an AI/ML focus, and 4+ years developing AI/ML products.
• Demonstrated experience building, training, evaluating and deploying AI/ML systems, not just publishing them.
• Experience with data collection, synthetic data generation and data quality evaluation.
• Ability to turn research ideas into working demos quickly and to collaborate across ML, hardware and embedded systems.

Required skills

• Building RL/agent environments and training with reinforcement learning.
• Fluency in Python, PyTorch and large-scale training pipelines on cloud or distributed systems (AWS, GCP).
• Strong knowledge of statistical hypothesis testing, experimental design and causal discovery.
• Preferred: deep expertise in time-series ML, signal processing and foundation models (Chronos, TimesFM, TimeGPT), parameter-efficient fine-tuning (LoRA/Q-LoRA) and DPO/RLAIF.

What we offer

• Expected new-hire wage range of $197,800 to $271,975, with a discretionary performance-based bonus.
• Medical, vision and dental coverage, 401k, paid vacation, holidays and sick time.
• First shift, days; about 10% travel required.