Machine Learning Manager (AI)

Location: Hybrid, Kuala Lumpur, Malaysia

Company

hirify.global develops consumer cybersecurity, privacy, identity protection, and financial wellness products, including MoneyLion, Norton, Avast, and LifeLock.

What you will do

• Lead, coach, and develop a machine learning and AI team while fostering ownership, technical excellence, and continuous learning.
• Set technical direction for ML and AI initiatives aligned with product and business priorities.
• Partner with Product, Engineering, Data, and platform teams to translate business problems into practical ML and AI solutions.
• Guide projects from exploration and experimentation through development, productionization, monitoring, and iteration.
• Establish standards for experimentation, model evaluation, reliability, maintainability, monitoring, governance, and scalable development workflows.
• Provide architecture and implementation guidance, communicate technical risks and opportunities, and evaluate modern approaches including LLM-based systems.

Requirements

• Experience leading machine learning or AI initiatives from idea to production and translating business problems into practical solutions.
• Experience managing, mentoring, and developing technical team members.
• Strong foundations 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.
• Ability to frame business problems, prioritize effectively, and guide teams toward practical, high-impact solutions.
• Strong communication and collaboration skills across technical and non-technical stakeholders.
• Comfort working in fast-paced, ambiguous environments while balancing execution, technical quality, and team growth.
• Experience with modern ML frameworks and tooling, MLOps workflows including model monitoring, CI/CD, and lifecycle management, plus cloud platforms and production infrastructure.
• Experience improving engineering standards, governance, and reusable internal capabilities across multiple ML projects.

Nice to have

• Exposure to natural language processing, search, recommendation systems, or modern GenAI and LLM application patterns.

Culture & Benefits

• Flexible working options, time off, competitive pay, benefits, and well-being programs.
• Culture of healthy debate, experimentation, continuous learning, ownership, and customer focus.
• Inclusive environment that values different experiences, identities, and ideas.

Hiring process

• Screening call.
• Take-home assessment.
• Hiring manager interview followed by a stakeholder chat.