Applied AI Software Engineer (Tech Lead - moment)

Job Description

About Cookpad

Cookpad is a food tech company dedicated to shaping the future of home cooking and food as a pillar for a sustainable future. We have been developing innovative product ideas and we have a new product launch in 5 countries: Japan, Indonesia, UK, France and Italy.

[moment] helps people learn to cook in an innovative way with a personal coaching service. This service is completely based in AI using multimodal (text, vision, audio).

Responsibilities

As a Applied AI Engineer, you will take on complex and intellectually stimulating challenges to dramatically enhance the quality of the user experience. You will not only be responsible for the technical realization of AI-driven experiences, but also play a key role in defining what kind of experiences we should create. By analyzing user learning challenges, behavioral data, and conversational logs within moment, you will identify the concrete tasks and user needs that AI should support. You will define requirements derived from user value and translate them into technical specifications.

Examples of Key Challenges

While there are multiple potential areas of responsibility, you will take ownership of one or more of the following core challenges—each of which requires a high level of technical and conceptual skill.

1. Designing and Implementing Advanced Task/Research Agents

You will build research agents designed to solve specific tasks. This involves defining mechanisms for managing the resources required to complete those tasks efficiently. You will establish systems that can identify, access, and process relevant contexts (e.g., past coaching histories), manage these resources, and generate final outputs. The focus is on efficient resource management—solving problems effectively without time constraints.

2. Identifying and Solving Fundamental Challenges in Cooking Video Understanding

You will tackle foundational challenges in understanding long-form video content, developing solutions that go beyond current limitations. This includes addressing core issues such as hallucination and context poisoning in video processing. You will also work on improving the accuracy of object detection and pixel-level analysis in computer vision tasks. Success in this area requires the ability to deeply understand the characteristics of target videos (frame rate, length, shooting style, etc.) and to ask the right questions to correctly define the nature of each problem.

3. Implementing a Sophisticated Multi-Layer Memory System for Conversational AI

You will design and build an advanced memory system that enables chatbots to maintain context and deliver a superior conversational experience. This will go beyond simple conversation summarization, integrating short-term memory (e.g., extracted entities) and long-term memory (e.g., user preferences and personalization), and using advanced techniques to build knowledge bases that solve real-world problems through, for example (but not limited to), graphs, semantic search, and hybrid approaches. Your goal is to orchestrate these multiple layers of memory to create a system far more advanced than the current one (which, for example, handles the last 25 conversation interactions), allowing dynamic updates to user preferences and context over time.

Requirements (Must-Haves )

• Approximately 5+ years of software development experience
• Strong professional proficiency in Python
• Understanding of modern development practices (TDD, version control, CI/CD, containerization, etc.)
• Hands-on experience developing and integrating applications using LLMs
• Practical knowledge of optimizing generative model outputs
• Ability to work effectively both independently and collaboratively
• Strong analytical curiosity to deeply understand the essence of a problem
• Proven success in dynamic, fast-paced environments
• Ability to iterate rapidly and build solutions for undefined, complex challenges
• Excellent English communication skills within cross-functional teams
• Experience deriving insights from user behavior or conversational data to inform AI design requirements
• Ability to translate user context and emotions into technical specifications
• Experience defining problems through UX research, data analysis, or user interviews

Preferred Qualifications

• Experience solving any of the key challenges listed above–or similarly complex technical problems
• Background in computer vision or traditional machine learning (especially with video data processing)
• Experience developing hybrid solutions combining modern generative AI and traditional methods
• Sensitivity to human–AI interaction nuances and user experience optimization
• Practical understanding of AI model trade-offs, performance, and constraints
• Experience with vector embeddings and vector databases (e.g., Pinecone)
• Experience implementing Retrieval-Augmented Generation (RAG) architectures for LLM-based applications
• Experience fine-tuning and customizing large language models using frameworks such as LangChain, LlamaIndex, Hugging Face, AWS Bedrock, or Google Vertex AI
• Experience developing in cloud environments (AWS, GCP, or Azure)
• Knowledge of MLOps / LLMOps (model deployment, serving, monitoring, etc.)
• Foundational understanding of data engineering, such as building data pipelines for AI applications

Location

〒153-0044 2-22-44, Ohashi, Meguro-ward, Tokyo