Senior AI Research Scientist

CTW; New York (NY); On-site; USD 180,000 - 240,000; Full time

Job summary

CTW in New York, NY seeks a Senior AI Research Scientist to bridge cutting-edge AI research with production engineering, building intelligent systems that drive measurable business impact. The role focuses on LLMs, AI Agents, and Multimodal AI to solve real-world challenges across our gaming platform.

You will transform advanced AI into scalable, production-ready solutions, collaborating with engineering and product teams to design, deploy, and optimize AI systems that automate workflows,

Qualifications

• Master's or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, Computational Linguistics, or a related field.
• 5+ years of industry or applied AI experience developing LLM, AI Agent, Multimodal AI, or text generation.
• Demonstrated experience owning AI projects end-to-end, from solution design and implementation to deployment, evaluation, and continuous improvement.
• Strong understanding of modern LLM ecosystems, including prompt engineering, RAG, tool calling, AI agents, model evaluation, or workflow orchestration.
• Proficiency with mainstream deep learning frameworks such as TensorFlow or PyTorch, and solid programming skills (e.g., Python).
• Excellent analytical and problem-solving skills with the ability to translate AI research into practical business applications.
• Experience building and deploying production AI Agent systems.
• Experience with deploying models on cloud platforms like AWS, Google Cloud, or Azure.
• Ability to read and comprehend academic literature in English; multilingual work background is a plus.

Responsibilities

• Design, develop, and deploy production-ready AI solutions based on LLMs, AI Agents, and Multimodal AI technologies.
• Lead end-to-end AI projects from solution design and technical architecture through implementation, deployment, evaluation, and continuous iteration.
• Build AI agents capable of automating complex business workflows and integrating seamlessly into existing engineering systems.
• Collaborate with engineering teams to ensure AI systems are production-ready with strong considerations for system integration, reliability, observability, evaluation, and maintainability.
• Research and develop multimodal AI capabilities for gaming applications, including game understanding, game QA automation, game-playing agents, and foundation models specialized for gaming scenarios.
• Evaluate emerging AI technologies and incorporate state-of-the-art LLM, Agent, and Multimodal techniques into practical business applications.
• Optimize AI system performance, scalability, inference cost, and deployment efficiency.
• Work cross-functionally with product, engineering, and business stakeholders to translate business needs into scalable AI solutions.
• Document technical designs, architecture decisions, and implementation best practices.

Skills

LLMs

AI Agents

Multimodal AI

Python

Problem solving

Analytical thinking

Research

Deployment

Cloud platforms

Team collaboration

Education

Master's or PhD in CS/AI/ML or related field

Tools

TensorFlow

PyTorch

AWS

GCP

Azure

Job description

As a Senior AI Research Scientist, you will bridge cutting‑edge AI research with production engineering to build intelligent systems that create measurable business impact. You will focus on applying Large Language Models (LLMs), AI Agents, and Multimodal AI to solve real-world challenges across our gaming platform.

Rather than conducting research in isolation, you will be responsible for transforming advanced AI capabilities into scalable, production‑ready systems. You will work closely with engineering and product teams to design, build, deploy, and continuously optimize AI solutions that automate business workflows, enhance operational efficiency, and power next-generation gaming experiences across the G123 platform.

• Design, develop, and deploy production-ready AI solutions based on LLMs, AI Agents, and Multimodal AI technologies.
• Lead end-to-end AI projects from solution design and technical architecture through implementation, deployment, evaluation, and continuous iteration.
• Build AI agents capable of automating complex business workflows and integrating seamlessly into existing engineering systems.
• Collaborate with engineering teams to ensure AI systems are production-ready with strong considerations for system integration, reliability, observability, evaluation, and maintainability.
• Research and develop multimodal AI capabilities for gaming applications, including game understanding, game QA automation, game-playing agents, and foundation models specialized for gaming scenarios.
• Evaluate emerging AI technologies and incorporate state-of-the-art LLM, Agent, and Multimodal techniques into practical business applications.
• Optimize AI system performance, scalability, inference cost, and deployment efficiency.
• Work cross-functionally with product, engineering, and business stakeholders to translate business needs into scalable AI solutions.
• Document technical designs, architecture decisions, and implementation best practices.
• Master's or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, Computational Linguistics, or a related field.
• 5+ years of industry or applied AI experience developing LLM, AI Agent, Multimodal AI, or text generation.
• Demonstrated experience owning AI projects end-to-end, from solution design and implementation to deployment, evaluation, and continuous improvement.
• Strong understanding of modern LLM ecosystems, including prompt engineering, RAG, tool calling, AI agents, model evaluation, or workflow orchestration.
• Proficiency with mainstream deep learning frameworks such as TensorFlow or PyTorch, and solid programming skills (e.g., Python).
• Excellent analytical and problem-solving skills with the ability to translate AI research into practical business applications.
• Experience building and deploying production AI Agent systems.
• Experience with deploying models on cloud platforms like AWS, Google Cloud, or Azure.
• Ability to read and comprehend academic literature in English; multilingual work background is a plus, as is experience working on large-scale complex systems or with multinational teams.

What Success Looks Like

Production Deployment of AI Agents

• Successfully deploy AI agents into production business workflows.
• Build scalable AI systems that integrate seamlessly with existing engineering infrastructure.
• Deliver measurable improvements in operational efficiency, automation, labor savings, and cost reduction.
• Ensure AI systems meet production standards for reliability, observability, evaluation, monitoring, and maintainability.

Multimodal AI for Gaming

• Develop and optimize multimodal AI capabilities tailored for gaming scenarios.
• Build AI solutions for game QA automation, intelligent game-playing agents, and interactive AI systems.
• Contribute to the development of gaming foundation models specialized in game understanding, reasoning, and interaction.