Principal Applied Scientist

Designworks Talent•Seattle, WA

1d•$250,000 - $350,000•Hybrid

About The Position

Our publicly traded client develops proprietary technology and analytics to deliver identity intelligence, powering critical solutions that help organizations operate confidently. Their solutions enable real-time identification and location of people, businesses, assets, and their relationships for risk mitigation, due diligence, fraud prevention, regulatory compliance, and customer acquisition. These solutions support frictionless commerce, enhance safety, reduce fraud, and lower related societal costs. Our client is looking for a collaborative and forward-thinking Principal Applied Scientist to join their Seattle-based AI team. In this role, your work will drive the research, development, and refinement of generative AI, agentic AI, and deep learning models and algorithms to address complex challenges in fraud detection, risk management, and identity verification. You’ll partner with a diverse team of scientists, engineers, and product leaders to build scalable solutions that solve meaningful real-world challenges. This is an opportunity for someone who enjoys balancing research, experimentation, and hands-on product impact in a fast-moving environment where curiosity, creativity, and continuous learning are valued.

Requirements

Ph.D. in Computer Science, Artificial Intelligence, or a related field with a focus on: generative AI, agentic AI, deep learning, reinforcement learning, and/or graph neural networks, or equivalent industry experience.
7+ years with Applied research in AI.
Experience with large language models (LLMs), agentic systems, reinforcement learning, and/or graph neural networks.
Successfully shipping AI-powered products (not just publishing or prototyping).
Hands-on experience designing and deploying agentic AI systems, including tool usage, function calling, planning, multi-agent orchestration, retrieval-augmented generation, and evaluating agent behavior in production environments.
Pre-training and/or fine-tuning foundational large language models.
Proficiency in programming languages such as Python or C++, along with expertise in AI frameworks (e.g., PyTorch, TensorFlow, JAX).
Deep understanding of transformer architectures, deep learning, and generative AI, with experience in natural language processing (NLP) for generative and agentic AI applications.
Experience building and deploying scalable AI/ML solutions in real-world applications, including those at national or global scales.
Demonstrated ability to drive projects forward independently with minimal guidance.
Ownership of ambiguous problem framing through research, prototyping, productionization, and post-launch iteration.

Nice To Haves

Familiarity with supervised fine-tuning, RLHF/DPO, LoRA/PEFT, distillation, and large-scale distributed training.
AWS certifications related to generative AI.
Published research findings at top-tier conferences and journals.

Responsibilities

Drive the research, development, and refinement of generative AI, agentic AI, and deep learning models and algorithms to address complex challenges in fraud detection, risk management, and identity verification.
Partner with a diverse team of scientists, engineers, and product leaders to build scalable solutions that solve meaningful real-world challenges.
Balance research, experimentation, and hands-on product impact in a fast-moving environment.
Transform ambiguous research ideas into reliable production systems.