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Gen Digital

Builds consumer security and financial tools

Lead AI Scientist

Engineering LeadershipConfirmed live in the last 24 hours
Full-timeKuala Lumpur, Federal Territory of Kuala Lumpur, MalaysiaNo salary listedHybrid

About the Job

Requirements

  • Demonstrated experience leading machine learning or AI initiatives from idea to production, with a track record of translating business problems into practical solutions.
  • Experience managing, mentoring, and developing technical team members.
  • A strong foundation in machine learning, experimentation, statistical thinking, and software engineering.
  • Good programming knowledge and strong hands-on familiarity with Python and SQL.
  • Experience developing, deploying, and operating machine learning systems in production.
  • The ability to frame business problems, prioritize effectively, and guide teams toward practical, high-impact solutions.
  • Strong communication and collaboration skills, with the ability to work effectively across technical and non-technical stakeholders.
  • Comfort operating in fast-paced and ambiguous environments while balancing execution, technical quality, and team growth.
  • Experience working with modern machine learning frameworks and tooling, with the ability to evaluate and apply the right technologies for different use cases.
  • Familiarity with modern MLOps tooling and production workflows, including model monitoring, continuous integration and continuous delivery, and lifecycle management.
  • Experience with cloud platforms and production infrastructure.
  • Experience improving engineering standards, governance, and reusable internal capabilities across multiple machine learning projects.

Responsibilities

  • Lead, coach, and develop a high-performing machine learning and AI team, fostering a culture of ownership, technical excellence, and continuous learning.
  • Shape the technical direction of machine learning and AI initiatives aligned with business priorities and product goals.
  • Partner closely with Product, Engineering, Data, and platform teams to frame business problems and translate them into machine learning and AI solutions.
  • Guide projects from early exploration and experimentation through development, production, monitoring, and iteration.
  • Drive strong standards in experimentation, model evaluation, reliability, maintainability, monitoring, and governance across the team’s work.
  • Support the team in designing scalable machine learning systems, workflows, and development practices that improve long-term delivery velocity.
  • Provide technical guidance on architecture, trade-offs, and implementation strategy without becoming a bottleneck for the team.
  • Communicate technical concepts, risks, and opportunities clearly to both technical and non-technical stakeholders.
  • Research, evaluate, and guide the practical adoption of new machine learning and AI ideas, including modern methods such as large language model-based systems, where they can create meaningful business value.
  • Help build repeatable capabilities, frameworks, and ways of working that enable multiple machine learning efforts to succeed over time, not just individual one-off projects.

Desired Qualifications

  • Exposure to natural language processing, search, recommendation systems, or modern generative AI and large language model application patterns.

About the Company

Gen Digital

Builds consumer security and financial tools

Gen Digital sells software and services that protect consumers' connected devices, personal information and finances. Its Norton, Avast and LifeLock brands cover antivirus, online privacy and identity protection, while MoneyLion adds financial tools and access to credit products. The software detects malicious activity, checks for exposed personal data and alerts customers to threats across computers and phones. It earns revenue from subscriptions, financial services and fees from partners that connect customers with financial products. With operating roots dating to 1982, the group has dual headquarters in Tempe, Arizona, and Prague, Czech Republic.

Company size
1,001-5,000
Company stage
IPO
Headquarters
Tempe, AZ
Founded
1982

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