TECH-MI/EN-102- Platform Engineer - AI Foundation

At LegalOn Technologies, the AI Foundation team is responsible for developing the machine learning infrastructure that supports the core AI capabilities of our products. This includes building domain-specific Adapted models and promoting AI engineering best practices within our product development teams. In this role, you will be responsible for developing and maintaining a flexible and reliable MLOps/LLMOps platform. You will also work closely with data scientists and ML engineers to understand their needs, provide technical leadership, and ensure those needs are met from a technical perspective. ■What mission or challenges will you take on? We build automated MLOps and LLMOps infrastructure and tools to streamline machine learning workflows and support the development of innovative ML projects across the company. ■What tasks will you undertake? - Development and maintenance of MLOps and LLMOps platforms, ensuring flexibility and reliability - Staying up to date with the latest advancements in machine learning and AI, particularly best practices in LLMOps - Collaboration with ML engineers, domain experts and SRE. - Optimization of data processing and model training pipelines - Implementation of automated testing and deployment for machine learning models For more details about our company, products, and development organization: https://legalforce-recruit.notion.site/LegalOn-Technologies-3e114a8aecfb410a96424e34a0ed8bd6 List of Research Achievements: https://legalforce-recruit.notion.site/Publications-LegalOn-Technologies-Research-4b91fec1eb7641a6a26f6df7794ad47a

- Bachelor's or Master's degree in Computer Science, Engineering, or a related field - 3+ years of backend development experience or equivalent skills - Proficiency in at least one programming language - Strong familiarity with MLOps and LLMOps principles and tools - Knowledge of software engineering best practices - Strong problem-solving, analytical, and communication skills - Japanese language proficiency equivalent to JLPT N2

- Experience working with machine learning using ecosystems like TensorFlow or PyTorch - Development experience with Python or Rust - Experience in server development using container technologies like Docker - Ability to utilize cloud infrastructure (AWS, GCP, Azure) following Infrastructure as Code (IaC) best practices - Experience collaborating across multiple teams to drive technical coordination and integration