Masuda Group is seeking a Machine Learning Engineer

Masuda Group is seeking a Machine Learning Engineer to design, train, and deploy production ML, NLP, and LLM systems across our Experience Management (XM) platforms and data infrastructure.

In this role, you will build automated text classification, sentiment and thematic extraction, respondent fraud detection, and predictive analytics pipelines handling high-throughput survey datasets and unstructured feedback.

Technical Environment

Languages & Frameworks:

• Python
• PyTorch
• Hugging Face Transformers
• Scikit-learn
• FastAPI

LLMs & Retrieval:

• Open-Source LLMs
• vLLM
• Vector Databases (pgvector, Qdrant)
• LangChain
• LlamaIndex

Data & Pipelines:

• Polars
• Pandas
• Apache Spark
• Apache Kafka

Databases:

• ClickHouse
• PostgreSQL
• Redis

MLOps & Cloud:

• MLflow
• Docker
• Kubernetes
• AWS SageMaker
• GCP Vertex AI
• Triton

CI/CD & IaC:

• GitHub Actions
• Terraform

Key Responsibilities

• Design, fine-tune, and evaluate machine learning and deep learning models for text classification, sentiment analysis, entity recognition, and thematic clustering.
• Develop real-time fraud detection and anomaly detection algorithms to identify bots, speeders, and low-quality responses across global panels.
• Build and scale low-latency model inference microservices and gRPC / REST endpoints using FastAPI, Triton, or vLLM.
• Deploy and maintain end-to-end MLOps pipelines covering experiment tracking, model registry, automated retraining, and data drift monitoring.
• Collaborate with backend engineers to integrate ML services into Java / Spring Boot and ClickHouse data architectures.
• Optimize model architectures for inference latency, memory footprint, and compute costs across AWS and GCP infrastructure.