Senior MLOps Engineer (Full Remote) in JAPAN

• Position: Senior Search Engineer
• Location: (Full remote work)
• Starting Salary Range: ~10M JPY
• Japanese level required: None

About the Company

Our product is not another chatbot. Our automated chat solution and conversational technology are changing the way consumers purchase or act online. We converts customers who appear "unengaged" to become "valuable" through designed chat on Messaging Apps. Using AI-powered, human-designed conversation flows across chat platforms, we enables brands to build personalized, automated conversations with their consumers and develop a deeper understanding of their preferences while creating a delightful, seamless shopping experience. Our last 3 years have been phenomenal. We have captured the heart of many businesses in Japan, with over 480 enterprises relying on our chat commerce offering to boost their mobile business.

The goal is simple: to “revolutionize hospitality on the Internet”, unlocking digital customer service experiences that were limited to physical stores previously.

With more than 480 enterprise companies worldwide already utilizing our product, we are perfectly poised to seize market share and fuel exponential growth in the US market, with an eye on global expansion. Investors have taken note of our potential, leading us to recently secure nearly $40 million in funding, backed by Salesforce Ventures.

Job Description

As a Senior MLOps Engineer, you will be at the forefront of deploying, optimizing, and monitoring LLMs in production environments. Your role will involve building and maintaining scalable pipelines, ensuring low-latency inference, and implementing best practices in monitoring and observability. You will also work with state-of-the-art tools like Hugging Face and MLFlow to fine-tune models and integrate them into robust AI solutions.

Roles and Responsibilities

• Model Deployment & Management: Build and maintain scalable pipelines for deploying LLMs with a focus on efficiency and low-latency inference. Leverage tools like Hugging Face and MLFlow for seamless integration and automate deployment processes, including validation and CI/CD.
• Monitoring & Observability: Implement monitoring frameworks to ensure model performance and reliability, utilizing advanced observability tools and deploying alert systems to address anomalies.
• Infrastructure Optimization: Design and optimize cloud and on-premise infrastructure for large-scale LLM operations, collaborating with providers like AWS, Azure, and GCP to balance cost and performance. Ensure seamless AI model integration into conversational platforms.
• Collaboration & Documentation: Align with AI engineers and data scientists on project goals, document MLOps processes and best practices, and provide training on methodologies and tools to maintain operational excellence.

Must Requirements:

• 5+ years of experience in MLOps, DevOps, or related fields, with a focus on deploying and managing LLMs or other large-scale machine learning models.
• Proven experience with tools like Hugging Face, MLFlow, and containerization technologies (Docker, Kubernetes).
• Strong experience with cloud platforms (AWS, Azure, GCP) and infrastructure as code (Terraform).
• Hands-on experience in reducing inference latency and optimizing AI infrastructure.

Technical Skills:

• Proficiency in Python, with experience in ML libraries such as TensorFlow, PyTorch, and related frameworks.
• Expertise in CI/CD pipelines, version control (Git), and orchestration tools.
• Familiarity with Generative AI, prompt engineering, and deploying models at scale.

Since we receive a large number of applications, we may not be able to respond to each applicant individually. Only shortlisted candidates will be contacted for further steps. Thank you for your understanding.

If you’re open to opportunities, we encourage you to apply as we have more positions available via our career site.