Machine Learning Operations (MLOps) Engineer

Location: Hanoi

Key Responsibilities:
● Design, build, and troubleshoot production-grade AI systems and applications on
GCP & AWS
● Develop and maintain CI/CD pipelines using tools like Jenkins, GitHub Actions, or
similar.
● Optimize, refactor, containerize, deploy, and monitor data science models, ensuring
robust versioning and quality control.
● Automate testing, validation, and performance evaluation of machine learning
models.
● Partner with data scientists, engineers, and architects to deliver scalable solutions,
documenting processes clearly and comprehensively.
● Manage and optimize infrastructure-as-code (IaC) using tools like Terraform or
CloudFormation to ensure scalable and reproducible environments.
● Implement and monitor model performance metrics in production, proactively addressing drift, bias, or degradation.
● Ensure security and compliance of AI systems, including data privacy standards (e.g., GDPR, HIPAA) and secure deployment practices.

Required Qualifications:
● Proven experience designing and implementing MLOps pipelines on cloud platforms
(Preferably GCP & AWS).
● Hands-on expertise with MLOps frameworks (e.g., Kubeflow, MLFlow, Metaflow,
Ray) and containerization tools (Docker, Kubernetes).
● Strong programming skills in Python, Bash, or similar, paired with deep knowledge of
Linux environments.
● Experience with monitoring tools like Prometheus, Grafana, or custom logging
frameworks for tracking system and model performance.
● Knowledge of distributed computing frameworks (e.g., Spark, Ray) for handling large-scale data processing or model training.
● Understanding of RESTful APIs and microservices architecture, with experience
integrating ML models into application ecosystems.
● Excellent English communication skills, with a collaborative, team-focused approach.
Preferred Qualifications:
● Experience with real-time data processing or edge computing.

● Background in AI/ML applications tied to neuroscience, wearables, or human-
computer interaction (aligned with EMOTIV’s mission).
Please share your CV to Ms Huyen at huyennguyen@emotiv.com.