Staff AI/ML Engineer, Deep Agentic Reasoning Engineer (Lorenz Labs)

Analog Devices; San Jose (CA); On-site; USD 198,000 - 272,000; Full time

Job summary

Analog Devices, Inc. seeks a Deep Agentic Reasoning Engineer to design and build multimodal reasoning models for Edge AI applications.

You will collaborate with experts across AI, NLP, audio, time series, and RL to advance agentic systems aligned with business needs. You will prototype in Python using PyTorch/TensorFlow, apply mid- and post-training techniques, and explore distillation to deploy efficient models.

Qualifications

• PhD in AI-related fields such as NLP, CV, or speech processing.
• 6+ years of experience releasing AI/ML products.
• Strong publication record in top-tier venues (e.g., NeurIPS, ICML, ICLR, ACL, CVPR).

Responsibilities

• Develop and evaluate multimodal deep learning models for classification and reasoning tasks.
• Engage in the full research lifecycle from data collection to rigorous evaluation.
• Prototype models in Python (PyTorch/TensorFlow) and implement reasoning improvements.
• Apply distillation to transfer capabilities from larger to smaller models.
• Document experiments and publish results in internal reports and top venues.

Skills

AI/ML Expertise

Publication record

Growth Mindset

Education

PhD in AI fields

Tools

PyTorch

TensorFlow

Transformer models

Reinforcement Learning

LangGraph

Job description

About Analog Devices

Analog Devices, Inc. (NASDAQ: ADI ) is a global semiconductor leader that bridges the physical and digital worlds to enable breakthroughs at the Intelligent Edge. ADI combines analog, digital, AI, and software technologies into solutions that combat climate change, reliably connect humans and the world, and help drive advancements in automation and robotics, mobility, healthcare, energy and data centers. With revenue of more than $11 billion in FY25, ADI ensures today's innovators stay Ahead of What's Possible. Learn more at www.analog.com and on LinkedIn and X .

About the Role

We're looking for Deep Agentic Reasoning Engineer (open rank) to design and build multimodal reasoning models (e.g., time-series, audio, video, sensor data) for Edge AI applications. You'll collaborate with experts in AI, NLP, audio, time series, RL and other domains to advance reasoning capabilities in alignment with Analog Devices business needs. This role offers the opportunity to work on the forefront of AI research, contributing to the development of agentic systems and multimodal reasoning frameworks.

What You'll Do

• Develop and Evaluate Models: build and evaluate deep learning models for multimodal classification and reasoning tasks.
• Full Research Stack: Engage in the full research lifecycle, including stakeholder discussions, data collection, annotation, preprocessing, model training, and rigorous evaluation.
• Prototype and Innovate: Prototype models in Python (using PyTorch/TensorFlow) and implement core reasoning improvements, including mid-training and post-training techniques for multimodal models.
• Knowledge Distillation: Apply distillation techniques to transfer reasoning capabilities from larger models to smaller, efficient models.
• Dissemination: Document experiments and results through internal reports, blog posts, and publications in top-tier conferences and workshops.

What You Bring

• AI/ML Expertise: 6+ years of experience releasing AI/ML products.
• Educational Background: PhD in AI-related fields such as NLP, Computer Vision, Speech Processing, or related discipline.
• Research Excellence: Strong publication record in top-tier venues (e.g., NeurIPS, ICML, ICLR, ACL, NAACL, EMNLP, CVPR).

Core Technical Expertise

• Proficiency in training, post-training, and evaluating transformer-based models with deep understanding of training dynamics, architecture modifications, and optimization techniques
• Strong expertise in supervised fine-tuning, RL (e.g., GRPO), and advanced post-training techniques for reasoning models, including hands-on experience with RL implementation and policy optimization
• Experience in implementing and modifying transformer architectures (encoder/decoder variants, attention mechanisms, positional encodings)
• Advanced knowledge of techniques including Chain-of-Thought (CoT), agentic tree search methods, continual learning, etc.
• Multi-agent orchestration, task decomposition, and experience with both static frameworks (e.g., LangGraph) and dynamic multi-agent harnesses for complex reasoning workflows

Growth Mindset

• Appetite for continuous learning with demonstrated ability to quickly adapt to new research directions
• Resourcefulness in exploring and implementing emerging paradigms such as JEPA training, world models, diffusion-based generation, and agentic harnesses
• Interest in frontier applications including edge AI deployment, multi-agent orchestration, deep research automation

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.

Analog Devices is an equal opportunity employer. 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 $197,800 to $271,975. 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 den