MTI Technology, established in 2016 as a subsidiary of MTI Group, specializes in creating and distributing mobile content and services through applications and web platforms, primarily for the Japanese market. With a growth from 20 to over 185 employees, the company focuses on content, healthcare, corporate DX support, and AI.
Their business model involves developing smart mobile content and services using agile methods, balancing excellence, feasibility, and convenience. Key products include 'Life…socket' for weather information APIs, 'Emot' for multi-modal route search and e-ticket functions for sightseeing, 'HoneyComb' for centralized weather information via GraphQL, 'music.jp' for music, video, and books, 'Luna Luna' for women's healthcare, '3D Amagumo Watch' for weather-related disaster reduction, 'CARADA' for physical data management, '&Pay' for smartphone payments, 'Carada Solamichi' for electronic medication history, and 'Atleta' for athlete self-management.
The company is committed to contributing to a smart and seamless future society and fosters a working environment that encourages learning, challenges, and problem-solving through teamwork and open communication. They also offer AI-powered digital transformation consulting services.
MTI Technology, established in 2016 as a subsidiary of MTI Group, specializes in creating and distributing mobile content and services through applications and web platforms, primarily for the Japanese market. With a growth from 20 to over 185 employees, the company focuses on content, healthcare, corporate DX support, and AI.
Their business model involves developing smart mobile content and services using agile methods, balancing excellence, feasibility, and convenience. Key products include 'Life…socket' for weather information APIs, 'Emot' for multi-modal route search and e-ticket functions for sightseeing, 'HoneyComb' for centralized weather information via GraphQL, 'music.jp' for music, video, and books, 'Luna Luna' for women's healthcare, '3D Amagumo Watch' for weather-related disaster reduction, 'CARADA' for physical data management, '&Pay' for smartphone payments, 'Carada Solamichi' for electronic medication history, and 'Atleta' for athlete self-management.
The company is committed to contributing to a smart and seamless future society and fosters a working environment that encourages learning, challenges, and problem-solving through teamwork and open communication. They also offer AI-powered digital transformation consulting services.
As a Mid-Level AI Engineer, you will build upon foundational knowledge to independently design, develop, and maintain AI systems. You are adept at leveraging machine learning algorithms and deep learning frameworks, capable of taking a specific project, breaking it down into necessary steps, and executing them autonomously. You serve as a crucial bridge between high-level concepts and detailed implementation, ensuring the successful execution of AI initiatives.
Key Responsibilities
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Collaborate closely with the project team, including the Senior AI Engineer/ SA providing architectural guidance, to contribute to key phases of the data science project lifecycle, from gathering business requirements to solution delivery, and deliver project outcomes to internal stakeholders or external customers.
Engages with clients to understand business needs, present findings, and align technical work with stakeholder goals.
Provides structured feedback to junior members, supports onboarding, and contributes to skill-building within the project team.
Developing scalable AI systems and designing/building algorithms that automate predictive data models.
Creating and managing the AI development and production infrastructure, including automating AI infrastructures for data science teams.
Participating in all phases of AI solutions development, from requirements definition and design to development, deployment, integration, maintenance, performance tuning, and monitoring.
Collaborating extensively with cross-functional teams, including data scientists, software engineers, and product managers, to define project requirements, ensure seamless progress, and facilitate AI adoption and best practices.
Driving scalability improvements and introducing new capabilities in machine learning platforms, often working across the full stack on tools and infrastructure that empower machine learning teams.
Required Skills & Qualifications
A Bachelor's degree in a technical field such as CS, AI, or Data Science, or equivalent practical experience. A Master’s degree is a plus.
3 years of professional experience
building and shipping software, with a focus on AI/ML systems.
Fluent in English with strong communication skills
, especially when engaging with non-technical business stakeholders
Familiarity with cloud platforms (AWS, Azure, GCP).
Proficiency with containerization (Docker, Kubernetes) and modern CI/CD practices for production environments.
Experience in building or prototyping features with GenAI capabilities (LLMs, Embeddings, Fine-Tuning) and core NLP concepts.
Experience in agentic frameworks (eg. LangChain, MCP, AutoGen) for building LLM-powered applications.
Experience with reinforcement learning, especially RLHF or applying RL to agent-based systems.
Able to communicate effectively within the team members.
The ability to work independently, troubleshoot complex issues, and mentor more junior team members is also expected.
Strong problem-solving skills and a data-driven mindset are fundamental.
Develop and Implement Evaluation Frameworks: The engineer will be responsible for creating and deploying frameworks to test and benchmark generative AI solutions for both quantitative and qualitative metrics
Experience with high-performance computing, GPU optimization, and building for low-latency environments is a strong plus.
