Job Overview
Location
Seattle
Job Type
Full-time
Category
Data Scientist
Date Posted
May 16, 2026
Full Job Description
đź“‹ Description
- • Develop and deploy generative AI and agentic AI systems to advance identity verification, fraud prevention, and risk intelligence solutions for a publicly traded software company.
- • Design and implement deep learning models—including transformer architectures, graph neural networks, and reinforcement learning systems—used in real-time identification of people, businesses, assets, and their relationships.
- • Collaborate with cross-functional teams of scientists, engineers, and product leaders to translate research into scalable, production-grade AI solutions that reduce fraud and support regulatory compliance.
- • Build and optimize agentic AI systems with capabilities in tool usage, function calling, planning, multi-agent orchestration, and retrieval-augmented generation (RAG), ensuring reliable performance in production environments.
- • Pre-train and fine-tune foundational large language models (LLMs), applying techniques such as supervised fine-tuning, RLHF, DPO, LoRA, PEFT, and model distillation to improve accuracy and efficiency.
- • Design and ship AI-powered products end-to-end, from concept and experimentation to deployment at national or global scales, ensuring robustness, scalability, and measurable business impact.
- • Evaluate agent behavior and model performance in live systems, using rigorous metrics to guide iterative improvements and maintain compliance with industry standards.
- • Apply expertise in natural language processing (NLP) to develop generative AI applications for identity intelligence, including entity resolution, relationship mapping, and anomaly detection.
- • Utilize Python and C++ with AI frameworks such as PyTorch, TensorFlow, or JAX to prototype, train, and deploy models in cloud-based environments.
- • Engage in continuous learning by reading cutting-edge research and rapidly translating findings into working prototypes, bridging the gap between academic innovation and product delivery.
- • Contribute to the development of scalable ML infrastructure, including distributed training pipelines and model serving systems optimized for low-latency, high-throughput use cases.
- • Participate in defining the technical roadmap for AI capabilities within the identity and risk intelligence platform, aligning research initiatives with business objectives and customer needs.
- • Maintain awareness of emerging trends in generative AI, agentic systems, and risk intelligence, ensuring the company's technology remains at the forefront of the industry.
- • Support the documentation and knowledge-sharing of AI models and systems to enable collaboration across engineering, data science, and product teams.
🎯 Requirements
- • Ph.D. in Computer Science, Artificial Intelligence, or a related field with focus on generative AI, agentic AI, deep learning, reinforcement learning, and/or graph neural networks—or equivalent industry experience
- • 3–6 years of applied research experience in AI with a track record of shipping AI-powered products (not just prototyping or publishing)
- • Hands-on experience designing and deploying agentic AI systems including tool usage, function calling, planning, multi-agent orchestration, and RAG
- • Proficiency in Python or C++ and AI frameworks such as PyTorch, TensorFlow, or JAX
- • Deep understanding of transformer architectures, LLMs, and NLP applications in generative and agentic contexts
- • Experience building and deploying scalable AI/ML solutions in real-world, production environments at national or global scale
🏖️ Benefits
- • Stock (RSU) grants
- • 401(k) with generous company match
- • Flexible PTO policy
- • Medical, dental, and vision coverage
- • Commuter benefits
- • In-office healthy snacks and team events
Skills & Technologies
About DesignWorks Talent
DesignWorks Talent is a boutique recruiting firm that places designers, researchers, product managers, and creative technologists in permanent and contract roles at technology, e-commerce, and consumer brands. Founded in San Francisco in 2016, the company maintains a curated network of senior-level talent and partners with venture-backed startups and Fortune 500 companies to build in-house design and product teams. Services include retained search, contingency placement, contract staffing, compensation benchmarking, and team-building advisory. The firm operates across North America and Europe while remaining focused on digital product, UX, brand, and service design disciplines.
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