The AI Engineer at Metthier Co., Ltd. is responsible for deploying, optimizing, and maintaining machine learning models as part of our AI solutions. This role involves collaborating with data engineers and scientists to ensure data availability, model development, and integration into various AI applications. In addition to technical work, the AI Engineer will conduct on-site work surveys and observations to gather real-world data and insights, ensuring AI models are tailored to practical applications. Strong communication skills are essential for effective collaboration with stakeholders and team members.
Responsibilities:
- Model Deployment and Optimization: Deploy, optimize, and maintain machine learning models to ensure accuracy, efficiency, and scalability for AI solutions.
- On-Site Surveys and Observations: Conduct site visits to observe and understand on-the-ground data, gathering insights to inform model adjustments and improvements.
- Collaboration with Data Teams: Work closely with data engineers and scientists to ensure seamless data accessibility and integration of models into AI solutions.
- Code Development and Maintenance: Develop, maintain, and document code for model training, testing, and deployment, ensuring high-quality and consistent outputs.
- Performance Monitoring and Troubleshooting: Continuously monitor model performance, troubleshoot issues, and refine models for optimal results.
- Documentation and Communication: Maintain detailed documentation for all models, code, and procedures, and effectively communicate technical information to stakeholders and team members.
Qualifications:
- Master’s degree in Machine Learning, Computer Science, or a related field.
- 2+ years of experience in backend or infrastructure support, with a focus on machine learning.
- Hands-on experience with machine learning, deep learning, and deploying models.
- Proficiency in Python and machine learning libraries such as PyTorch and TensorFlow.
- Familiarity with cloud platforms such as Google Cloud, Azure, or AWS.
- Basic knowledge of RAG technologies, LLM frameworks, and vector databases.
- Experience with Kubernetes and containerized environments for model deployment.
- Proficiency in building and managing AI/ML solutions with ML Ops and CI/CD automation in cloud environments.
- Has excellent communication skills for effectively discussing technical concepts with both technical and non-technical stakeholders.
- Works well with others, shares expertise, and learns from team members, adapting quickly in a dynamic environment.