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Vi
EMOTIV TECHNOLOGY VIETNAM
Machine Learning Operations (MLOps) Engineer
Quận Nam Từ Liêm, Hà Nội
Số 6 Nguyễn Hoàng, tòa Dolphin Plaza, Phường Mỹ Đình 2, Quận Nam Từ Liêm, Thành phố Hà Nội
Theo dõi
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Đăng 2 ngày trước
và Công việc hết hạn trong 3 tuần tới
Docker
Machine Learning
AWS
Năm kinh nghiệm tối thiểu
Từ 1 năm
Cấp bậc
Junior
,
Middle
Loại hình
Remote
,
In Office
Loại hợp đồng
Fulltime
SALARY
Negotiable
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.
REQUIREMENTS
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] 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).
RECRUITMENT PROGRESS
ROUND 1: HR screening
ROUND 2: Technical assesment
ROUND 3: Research side assesment
ROUND 4: Offer
BENEFIT
Attractive Compensation and Time Off
Healthcare Insurance
Company activities (team building, company trip on working days)
Passionate colleagues
Flexible working time
Development Opportunities
Energetic, open, creative and transparent working environment
Chance to learn about and work on the latest neurotechnology
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