Senior Principal AI/ML Engineer, Deep Agentic Reasoning

Analog Devices

. Design and build multimodal reasoning models for Edge AI applications, including time-series, audio, video, and sensor data .

Posted 10/14/2026full-timeUnited StatesSenior💰 $260,360 - $357,995 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and building multimodal reasoning models for Edge AI applications, with a strong focus on deep learning, AI/ML product development, and advanced reasoning techniques. Proficient in Python, PyTorch, and TensorFlow, with a solid publication record in top-tier AI conferences.

Highest-signal resume keywords

Deep Learning Model DevelopmentMultimodal Reasoning TechniquesTransformer-Based Model TrainingAI/ML Product Release ExperiencePhD in AI-Related Fields

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Multimodal ClassificationReinforcement LearningSupervised Fine-TuningModel EvaluationKnowledge DistillationArchitecture ModificationsOptimization TechniquesChain-of-Thought (CoT)Policy OptimizationTask Decomposition

Soft Skills

CollaborationAdaptabilityCommunication

Tools & Technologies

PythonPyTorchTensorFlowLangGraphMulti-Agent Orchestration

Industry Keywords

Edge AIAI/ML SuccessResearch LifecyclePublication RecordEmerging Paradigms

Tech Stack

Tools & technologies

PythonPyTorchTensorflow

About the role

Key responsibilities & impact

Design and build multimodal reasoning models for Edge AI applications, including time-series, audio, video, and sensor data
Collaborate with experts in AI, NLP, audio, time series, RL, and other domains
Advance reasoning capabilities in alignment with Analog Devices business needs
Build and evaluate deep learning models for multimodal classification and reasoning tasks
Engage in the full research lifecycle, including stakeholder discussions, data collection, annotation, preprocessing, model training, and rigorous evaluation
Prototype models in Python using PyTorch/TensorFlow
Implement core reasoning improvements, including mid-training and post-training techniques for multimodal models
Apply knowledge distillation techniques to transfer reasoning capabilities from larger models to smaller, efficient models
Document experiments and results through internal reports, blog posts, and publications in top-tier conferences and workshops

Requirements

What you’ll need

15+ years of experience releasing software products with a strong track record of AI/ML success
6+ years of experience releasing AI/ML products
PhD in AI-related fields such as NLP, Computer Vision, Speech Processing, or a related discipline
Strong publication record in top-tier venues such as NeurIPS, ICML, ICLR, ACL, NAACL, EMNLP, and CVPR
Proficiency in training, post-training, and evaluating transformer-based models
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
Hands-on experience with RL implementation and policy optimization
Experience implementing and modifying transformer architectures, including encoder/decoder variants, attention mechanisms, and positional encodings
Advanced knowledge of Chain-of-Thought (CoT), agentic tree search methods, and continual learning
Experience with multi-agent orchestration and task decomposition
Experience with static frameworks such as LangGraph and dynamic multi-agent harnesses
Ability to quickly adapt to new research directions
Experience or resourcefulness exploring 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, and deep research automation
Applicants who are not US Citizens, US Permanent Residents, or protected individuals may be required to undergo an export licensing review process
Required travel of 10% of the time

Benefits

Comp & perks

Discretionary performance-based bonus based on personal and company factors
Medical coverage
Vision coverage
Dental coverage
401(k)
Paid vacation
Paid holidays
Sick time
Other benefits