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

We need to output HTML fragment with sections: About the role? Actually the posting includes "About The Role" heading. We need to use

for section headings like About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. We must not repeat job title as heading. We need to include sections only if posting has real specific content. We have content: "About The Role" (description). Then "What You’ll Do" (responsibilities). Then "What You Bring" (requirements/qualifications/skills). Then there is pay range and benefits info. Also there is "Required Travel: Yes, 10% of the time" and "Shift Type: 1st Shift/Days". Also there is mention of export licensing etc (legal boilerplate) which we should remove. Also EEO boilerplate remove. Also "Job Req Type: Experienced" maybe minor metadata; we can fold into short p or drop. We need to avoid cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions. Thus we need sections: About the role (maybe from "About The Role" paragraph). Responsibilities (from "What You’ll Do"). Requirements/Qualifications/Skills (from "What You Bring"). Benefits (from "This position includes medical, vision and dental coverage, 401k, paid vacation, holidays, and sick time, and other benefits.") Pay (from "The expected wage range for a new hire into this position is $230,000 to $316,250. 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.") Schedule (maybe from "Required Travel: Yes, 10% of the time Shift Type: 1st Shift/Days". That's schedule info. Could be considered schedule. We'll include schedule section. We must not include headings with filler like "commensurate with experience". Not present. We need to use

for each section heading. Use

• for any list of duties/requirements/benefits. The responsibilities are bullet-like sentences; we can make
  • . Similarly for requirements we can list bullet points. Benefits also list. We need to preserve all substantive information; do not invent or summarize away detail. So we need to keep the details exactly as in text, but we can format as list items. We must not repeat job title as heading. Not needed. We must not put Job ID/requisition numbers as headings; we can drop them. We need to output only HTML fragment, no /, no markdown fences. Let's extract content. About The Role paragraph: "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." That's the about role. Responsibilities (What You’ll Do): list: - 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. We need to keep the colon headings? Might keep as part of list item text. Requirements/Qualifications/Skills (What You Bring): list: - 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 We could flatten into bullet list items each line. Benefits: "This position includes medical, vision and dental coverage, 401k, paid vacation, holidays, and sick time, and other benefits." Pay: "The expected wage range for a new hire into this position is $230,000 to $316,250. 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." Schedule: "Required Travel: Yes, 10% of the time Shift Type: 1st Shift/Days" We might also include "Shift Type: 1st Shift/Days" as schedule. We need to avoid duplication. Ensure we don't include legal/EEO lines. Now produce HTML:

    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.

    Responsibilities

    • 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.

    Requirements

    • 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
    But nesting ul inside li may be okay but maybe better to keep flat list with dash? However spec says use
    • for any list of duties/requirements/benefits. It didn't forbid nested lists. Could keep simple flat list with each bullet as a line; but we have subpoints. Could still flatten: each subpoint as separate li. Might be okay. Simplify: just list each requirement as separate li, no nesting. Thus:

      Requirements

      • 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).
      • 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.
      • 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.
      That covers. Benefits:

      Benefits

      • Medical, vision and dental coverage
      • 401k
      • Paid vacation