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Salary
≈ $31k – $70k per year (Estimated)
Location
In office (Metro Gate Indang)
Seniority
Staff

Confirmed on the employer's own hiring board on Oct 15, 2026. First seen by Alion on Sep 5, 2026.

Overview
Company
Impact
Profile match
Maya, formerly PayMaya, is a Philippine digital financial services company operating a wallet and a digital bank. It provides payments, savings, credit and merchant acquiring for consumers and businesses. The company is part of the PLDT affiliated Voyager Innovations group.

What you will be doing:

  • Lead applied AI research and develop innovative machine learning, optimization, and data-driven solutions across Maya's AI initiatives.
  • Translate complex business problems into production-ready AI, machine learning, and optimization solutions.
  • Design, prototype, validate, and deploy scalable models and systems that deliver measurable business impact.
  • Drive the adoption of emerging AI technologies and research advancements, including Causal AI and Neuro-symbolic AI.
  • Partner closely with Product, Engineering, and Business teams to bring research innovations into production.
  • Lead and grow a high-performing AI research team, providing technical direction, mentorship, and strategic leadership.
  • Define and execute research roadmaps aligned with business priorities and Maya's AI strategy.
  • Represent Maya in the AI research community through academic partnerships, publications, and participation in leading AI/ML conferences.
  • Drive improvements across lending, fraud, marketing, and intelligent operations through innovative AI solutions, faster deployment of research, and increased adoption of frontier AI techniques.

What we are looking for:

  • Master's degree or PhD in Statistics, Mathematics, Computer Science, or a related quantitative field.
  • Experience in Data Science, Machine Learning, AI Research, or a related field.
  • Experience leading and managing high-performing Data Science teams.
  • Proven track record of delivering impactful AI or Data Science solutions in fast-paced environments.
  • Strong analytical and problem-solving skills with the ability to design innovative solutions while balancing business, regulatory, and responsible AI requirements.
  • Publication record or demonstrated research contributions through conference papers, workshops, or pre-prints is an advantage.

Displayed Skill Mastery:

  • Proven leadership, people management, and stakeholder management skills.
  • Ability to lead, mentor, and develop high-performing teams.
  • Strong communication, presentation, and interpersonal skills.
  • Experience working in agile environments and managing complex projects.
  • Ability to balance hands-on technical contributions with leadership responsibilities across multiple AI research domains.

Specialization Track A: LLMs, Audio Processing & Speech AI

  • Experience developing and fine-tuning speech, audio, and language models in research or production environments.
  • Strong knowledge of speech recognition, speaker verification, emotion recognition, audio classification, and speech-based behavioral modeling.
  • Experience with transformer-based architectures, multimodal learning, self-supervised learning, and representation learning.
  • Strong proficiency in PyTorch, TensorFlow, digital signal processing, feature engineering, and deep learning architectures such as Transformers, CNNs, and RNNs.
  • Familiarity with Causal AI and Neuro-symbolic AI approaches.
  • Background in behavioral science, psychology, psychometrics, or behavioral modeling is a plus.

Specialization Track B: Operations Research & Optimization

  • Strong background in Operations Research, Optimization, or Applied Mathematics.
  • Experience solving complex optimization problems, including linear programming, mixed-integer programming, multi-objective optimization, scheduling, routing, and resource allocation.
  • Experience developing algorithms, heuristics, simulation models, and decision-support systems.
  • Proficiency with optimization tools such as Gurobi, CPLEX, OR-Tools, SCIP, or similar platforms.
  • Strong understanding of mathematical modeling, algorithms, and computational complexity.
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