KEY RESPONSIBILITIES

Scrum Process Management for AI/ML Teams

• Facilitate Scrum ceremonies tailored to AI/ML development cycles (experimentation sprints, model training iterations)
• Adapt Scrum framework to accommodate the unique aspects of AI research and development
• Manage Sprint Planning for both research tasks and engineering deliverables
• Help the team achieve the Sprint Goal with the Definition of Done
• Ensure the team delivers the Increment with the agreed Definition of Done
• Support team in balancing exploration (research) and exploitation (production) activities
• Facilitate Daily Scrum with focus on model performance metrics and experiment results
• Work with other Scrum Masters to increase the effectiveness of Scrum implementation across the organization

Scaled Agile Framework Implementation

• Coordinate cross-team Sprint Planning for integrated AI solutions (PI Planning in SAFe)
• Facilitate multi-team Sprint Review and System Demo for AI products
• Implement Communities of Practice for AI/ML knowledge sharing
• Participate actively in Scrum Master Community of Practice
• Enable feature teams to work on end-to-end AI solutions
• Support Product Backlog Refinement across multiple teams
• Foster team self-management and cross-team coordination
• Champion whole-product focus and systems thinking

Data & AI Project Coordination

• Collaborate with Data Scientists and ML Engineers to define clear Definition of Done for AI models
• Support establishment of ML pipeline workflows and CI/CD for model deployment
• Coordinate between data engineering team and model development team
• With the team, manage dependencies between data collection, preprocessing, model training, and deployment phases
• Track and report metrics using data-driven approaches

Stakeholder Management in AI Context

• Communicate complex AI/ML concepts and progress to non-technical stakeholders
• Facilitate collaboration between business stakeholders and technical teams on AI requirements
• Manage expectations regarding AI capabilities and limitations
• Support definition of success metrics for AI initiatives

Team Development & Enablement

• Coach team on Agile practices within AI/ML development context
• Promote knowledge sharing on ML best practices and emerging techniques
• Build culture of experimentation and data-driven decision making
• Build a trusting and safe environment where problems can be raised without fear of blame, retribution, or being judged
• Create psychological safety for experimentation failures and learning from mistakes
• Pay attention to the motivation of team members daily and improve motivation for any low-motivated members
• Help build a productive environment where team members "own" the product and enjoy working on it
• Support cross-functional collaboration between data scientists, engineers, and domain experts
• Identify and address skill gaps within the team
• Motivate and encourage the team to improve continuously

Risk & Impediment Management for AI Projects

• Identify and mitigate risks specific to AI projects
• Remove blockers related to data access, computational resources, and tools
• Manage technical debt in ML pipelines and model versioning
• Coordinate with IT/DevOps to ensure adequate infrastructure for training and deployment
• Address ethical and compliance considerations in AI development

REQUIREMENTS

Education & Certifications

• Bachelor’s degree in computer science, Data Science, Mathematics, or related field
• Certified Scrum Master (CSM) or Professional Scrum Master (PSM) certification required
• Advanced certifications (PSM II/III, CSP-SM, SAFe Scrum Master) highly preferred
• Additional certifications in AI/ML or Data Science are significant advantages
• Continuous learning mindset with demonstrated courses in AI/ML fundamentals

Experience

• Minimum 3-4 years’ experience as Scrum Master, preferably in AI/ML or data-driven projects
• Experience with cross-functional teams of 5-9 members including data scientists and ML engineers
• Proven track record of successful AI/ML project delivery from experimentation to production
• Experience with Agile at scale frameworks (SAFe, LeSS) for multiple AI teams
• Proficiency with Agile tools: Jira, Azure DevOps, or similar
• Basic understanding of statistics, ML lifecycle, ML metrics, AI/ML tools and platforms, and A/B testing frameworks
• Understanding of CI/CD pipelines for ML models, version control for code and data
• Hands-on experience with MLOps practices and continuous delivery for ML models
• Background in managing teams working on both research and production environments

Domain Knowledge

• Understanding of Research vs Production mindset in AI development
• Familiarity with different AI domains (NLP, Computer Vision, Time Series, Reinforcement Learning)
• Knowledge of AI Ethics and Responsible AI principles
• Understanding of AI regulations and compliance requirements
• Awareness of intellectual property considerations in AI development

Soft Skills

• Excellent communication skills to bridge gap between technical and business teams
• Strong facilitation skills for technical discussions and decision-making processes
• Analytical mindset with ability to understand and communicate data-driven metrics
• High adaptability to work in fast-paced, research-oriented, and ambiguous environments
• Patience and persistence when dealing with iterative nature of AI development
• Leadership skills with servant-leader approach and growth mindset
• Conflict resolution and negotiation skills for cross-functional team dynamics
• Fluent English communication (verbal and written) for international collaboration
• Curiosity and passion for emerging AI technologies and methodologies
• Ability to manage stakeholder expectations in uncertain research outcomes

WHAT WE OFFER

Compensation & Benefits

• Competitive salary commensurate with experience and expertise
• 13th-month salary and performance bonus
• Comprehensive health insurance
• Annual health checkup and wellness programs
• Lunch allowance and monthly gasoline/transportation allowance
• Professional development budget for certifications and conferences
• Technical certificate fee sponsorship (full coverage for approved certifications)
• Social and Unemployment Insurance based on full contractual salary

Work Environment

• 5 working days per week (Monday to Friday) with flexible working hours
• Core hours 08:30 - 17:30 with flexibility for personal needs
• Hybrid working model: 2 days WFH (work from home) per week
• Access to latest AI/ML tools, platforms, and GPU clusters
• Collaborative and innovative team culture
• Dedicated experimentation time (20% for personal Kaizen/ project Kaizen)
• 12 days annual leave plus 2 additional company leave days
• National holidays according to Vietnam Labor Code

Growth Opportunities

• Clear career progression: Senior Scrum Master →Agile Coach
• Opportunity to work with cutting-edge AI technologies and methodologies
• Participation in AI research projects and academic publications
• International collaboration with AI experts and research institutions
• Regular tech talks and knowledge sharing sessions with industry leaders
• Mentorship program with senior AI practitioners
• Opportunity to speak at conferences and represent the company

Additional Perks

• Quarterly skill-up learning budget for team members to attend workshops, courses, or certifications
• Quarterly team building activities
• Sports clubs (badminton, yoga, football, table tennis…) with company-sponsored funding support
• Monthly Happy Hour
• Annual company retreat to exotic locations

HOW TO APPLY

Interested candidates please send your application to: Recruitment@mti-tech.vn

Please include:

• Updated CV/Resume with AI/ML project highlights
• Cover letter explaining your interest and experience in Scrum Master position and AI/ML domain
• Links to relevant certifications, portfolio, or GitHub projects
• Earliest availability to start
• References from previous AI.DI Lab team members (optional)