Staff AI/ML Engineer, Time-Series & Sensor Reasoning Models (Lorenz Labs)
Analog Devices15 days ago
Base Salary
$198k - $272k/yr
Responsibilities
- Lead R&D on intelligent time-series agents and foundation models for anomaly detection, reasoning, forecasting, and multimodal sensor understanding.
- Advance sensor fusion and cross-modal alignment across electrical, acoustic, inertial, photonic, physiological, text, and image modalities.
- Create benchmarking pipelines for time-series foundation models, including representation robustness, interpretability, and hardware performance metrics.
- Apply LoRA, Q-LoRA, adapter tuning, contrastive alignment, DPO, and RLAIF to multimodal sensor datasets and physical reasoning tasks.
- Research time-series embeddings, compression, motif discovery, memory, retrieval-augmented generation, and agentic systems for edge reasoning.
- Partner with hardware, signal-processing, systems, and embedded teams to co-design real-time, energy-efficient sensing architectures.
- Design statistical experiments for subject-matter experts to collect sensor data for model development.
- Publish and present research at ML and signal-processing venues and mentor junior researchers.
- Help shape Lorenz Labs’ foundation-model strategy for systems that understand and reason about physical environments.
Requirements
- At least 6 years of experience developing software products with an AI/ML focus and at least 4 years developing AI/ML products.
- Deep expertise in time-series machine learning, signal processing, and foundation models, including hands-on training or fine-tuning of time-series foundation models such as Chronos, TimesFM, or TimeGPT.
- Proficiency in representation learning, time-series encoding and compression, and motif discovery in high-dimensional temporal data.
- Knowledge of time-series reasoning models, cross-attention, multimodal embeddings, time-series agents, time-series memory, and RAG.
- Experience with parameter-efficient fine-tuning, LoRA/Q-LoRA, and reward-based optimization methods including DPO, PPO, and RLAIF.
- Strong knowledge of statistical hypothesis testing, experimental design, and causal discovery.
- Fluency in Python, PyTorch, and large-scale training pipelines using cloud or distributed systems such as AWS or GCP.
- Ability to collaborate across ML, hardware, signal-processing, and embedded-systems disciplines and translate research into deployable physical-intelligence systems.
- Preferred experience combining technical solutions with business problems, particularly for embedded systems.
- Preferred record of innovation through patents, publications, or open-source contributions.
Benefits
- Medical, vision, and dental coverage.
- 401(k), paid vacation, holidays, and sick time.
- Discretionary performance-based bonus.
- Required travel of approximately 10% of the time.
- First-shift/day schedule.
- Export licensing review may be required for applicants who are not U.S. citizens, permanent residents, or protected individuals when the position involves technical data.
Tech Stack
Categories
AI ResearchML Engineering
About Analog Devices
Analog Devices, Inc. designs and sells analog, mixed-signal, RF, power, sensor, and digital signal processing ICs to OEMs across industrial, automotive, communications, consumer, and healthcare markets. Founded in 1965 and headquartered in Wilmington, Massachusetts, the NASDAQ-listed company earns revenue from catalog and application-specific semiconductors and supporting software used in applications from factory automation and vehicles to data centers and medical devices.