AI/MLOps & Data Engineering Lead

ABOUT CLIENT

Our client is a big fintech company from Japan

JOB DESCRIPTION

We are in need of an AI/MLOps & Data Engineering Lead who possesses strong AI and Data skills. Suitable candidates will join a dynamic and proficient team to improve the quality of products serving a large customer base.
Key responsibilities include:
Developing and overseeing cross-company data infrastructure
Managing data integration and pipelines
Collecting data from different internal sources into a data lake
Distributing collected data to analysis and ML platforms
Establishing and managing data analysis infrastructure
Optimizing DWH performance
Ensuring data quality.

JOB REQUIREMENT

Educational background
Completed studies at a university/college in Vietnam
Major in mathematics, computer science or related field
 
Technical skill
AI software development
Experienced in developing AI algorithms or understanding their foundational principles
Developed an Application Programming Interface [API] as an internet service
Operated and manipulated API services using appropriate software
Measured performance using metrics software
Controlled and tuned accuracy through data operation
Data engineering
Development experience with Python and SQL (BigQuery preferred)
Experience in development and operation using AWS and Google Cloud or similar platforms
Tools
Configuration management: Terraform
CI/CD: GitHub Actions
Monitoring and logging: Datadog, Cloud Monitoring, CloudWatch
Project management: JIRA Cloud, Miro
Documentation: Kibela, Google Workspace
Spark: 2-3 years of experience
Airflow: 1 year (user role, not administrator)
Cloud architecture
Experienced in system development using cloud services on AWS, GCP or Azure (AWS preferred)
Understanding of cloud service components from an architectural perspective
Designed and integrated systems with appropriate security
Human skill
Experience in Project Manager [PM] or Product Manager [PdM] roles
Worked as a Data engineer lead of a team of at least 2 members for a period of time
Communication skill
Open-minded
Capable of understanding requirements and their purpose
Proficient in English (IELTS 7, TOEIC 800 or equivalent)

WHAT'S ON OFFER

Benefits for Employees:
Employees have the flexibility to work two days in the office and three days from home
Work hours are flexible, with the option to start between 8AM-9AM from Monday to Friday
Full salary during the probation period
Eligibility for various insurance benefits, including social, health, and unemployment insurance, as well as private health and accident insurance
Additional perks such as a 13th-month salary, 16-24 paid days off, and paternity leave
Opportunities for annual company trips, quarterly team building activities, and participation in billiards and running clubs
Access to an annual health check and well-equipped facilities, including a MacBook Pro and additional monitor
Career Growth and Development Support:
Clearly defined career paths for employees
Sponsorship for foreign language and international technology-related certifications
Access to both internal and external training courses, soft-skill workshops, and tech seminars
Recognition awards and biannual performance and salary reviews (in June and December)

CONTACT

PEGASI – IT Recruitment Consultancy | Email: recruit@pegasi.com.vn | Tel: +84 28 3622 8666
We are PEGASI – IT Recruitment Consultancy in Vietnam. If you are looking for new opportunity for your career path, kindly visit our website www.pegasi.com.vn for your reference. Thank you!

Job Summary

Company Type:

Product, Fintech

Technical Skills:

Data Engineering

Location:

Ho Chi Minh - Viet Nam

Working Policy:

Hybrid

Salary:

Negotiation

Job ID:

J01644

Status:

Close

Related Job:

Senior Deep Learning Engineer - AI for Wireless Systems

Ho Chi Minh, Ha Noi - Viet Nam

Computer Hardware

  • Machine Learning

Develop and test deep learning models for various wireless signal processing tasks including channel estimation, beam alignment, link adaptation, and scheduling. Utilize simulation tools and real-world datasets to create models that can be applied across different wireless scenarios. Build, train, and assess neural networks (e.g., CNNs, Transformers, GNNs) with PyTorch or TensorFlow. Engage in teamwork with researchers and system engineers to incorporate models into complete RAN systems. Enhance model efficiency for real-time processing and hardware acceleration. Participate in model assessment, performance comparison, and deployment preparation on GPU platforms.

Negotiation

View details

Engineering Manager - AI for RAN and 6G Wireless Systems

Ho Chi Minh, Ha Noi - Viet Nam

Computer Hardware

  • Machine Learning
  • Management

Manage and expand an engineering team focused on AI-enabled signal processing for the Radio Access Network (RAN). Supervise the development of deep learning models for various tasks related to RAN. Work with global teams to drive proof-of-concepts and production-quality AI-RAN components. Supervise the integration of AI models into full-stack simulations and/or testbeds using various frameworks. Align project priorities with hardware-software co-design constraints and deployment scenarios. Provide mentorship and guidance to team members, ensure technical excellence, and contribute to strategic direction.

Negotiation

View details

Director Engineering – Software Engineering and AI Inferencing Platforms

Ho Chi Minh, Ha Noi - Viet Nam

Computer Hardware

  • Management
  • Backend
  • Cloud
  • Data Engineering
  • AI

Lead and expand engineering teams in Vietnam across system software, data science, and AI platforms. Drive the creation, structure, and delivery of high-performance system software platforms that support AI products and services. Collaborate with global teams across Machine Learning, Inference Services, and Hardware/Software integration to guarantee performance, reliability, and scalability. Oversee the development and optimization of AI delivery platforms in Vietnam, including NIMs, Blueprints, and other flagship services. Collaborate with open-source and enterprise data and workflow ecosystems to advance accelerated AI factory, data science, and data engineering workloads. Promote continuous integration, continuous delivery, and engineering best practices across multi-site R&D Centers. Work with product management and other stakeholders to ensure enterprise readiness and customer impact. Establish and implement standard processes for large-scale, distributed system testing including stress, scale, failover, and resiliency testing. Ensure security and compliance testing aligns with industry standards for cloud and data center products. Mentor and develop talent within the organization, fostering a culture of quality and continuous improvement.

Negotiation

View details