Maya
At Maya , we’re building the future of fintech in the Philippines—and frontier AI research is at the heart of that mission . We’re looking for a Senior Research Scientist to join our Research & Development team , the engine that translates cutting-edge AI research into real-world impact across Maya’s products, customers, and operations. This is not a traditional delivery or analytics role . It is a research function with a clear mandate: identify, adapt, and transform advances from academic and industry AI research into production-grade systems at scale. You’ll operate at the intersection of scientific rigor and applied fintech impact , bridging theory and practice. Research Focus Areas Candidates may specialize in one or more of the following: Large Language Models (LLMs) Audio Processing / Speech AI Operations Research & Optimization (Decision Science) Causal AI Neuro-symbolic AI What You’ll Do As a Senior Research Scientist at Maya, you will: Lead applied research to develop novel algorithms, models, and AI-driven solutions Translate business and operational challenges into mathematical formulations, ML systems, or optimization frameworks Design, implement, and evaluate production-grade research outputs Rapidly prototype and experimentally validate new ideas Collaborate with engineering and product teams to deploy scalable, real-world systems Stay at the frontier of state-of-the-art AI/ML research and integrate relevant advances Build and sustain academic collaborations with universities and research institutions Contribute to Maya’s scientific footprint through publications and presentations at respected AI/ML venues (e.g., NeurIPS, ICML, ACL, Interspeech, AAAI) Explore frontier paradigms such as Causal AI and neuro-symbolic AI to build more robust, interpretable, and generalizable fintech solutions Mentor junior researchers and contribute to technical and research strategy Specialization Tracks Track A: LLM & / or Audio Processing / Speech AI Research & Responsibilities Develop and fine-tune speech, audio, and language models Design end-to-end pipelines for training, evaluation, and deployment of audio and multimodal models Extract and model audio features (acoustic, prosodic, paralinguistic) Build systems for: Automatic Speech Recognition (ASR) Speaker recognition and verification Emotion recognition from speech Audio classification and event detection Speech-based behavioral or psychometric modeling Methods & Techniques Transformer-based architectures (e.g., wav2vec, Whisper-style models) Self-supervised learning for audio Multimodal learning (audio + text) Representation learning and embedding methods Performance, latency, and scalability optimization What We’re Looking For Strong experience with PyTorch or TensorFlow Hands-on experience with LLMs, speech, or audio models in research and/or production Solid foundations in: Digital signal processing Audio feature extraction (MFCCs, spectrograms, embeddings) Deep learning for sequence data (Transformers, CNNs, RNNs) Emerging AI paradigms : familiarity with Causal AI and neuro-symbolic approaches, especially for interpretability and decision-making in high-stakes financial systems Preferred : experience or collaboration in behavioral science, psychology, or psychometrics (particularly for credit, engagement, or voice-based modeling) Track B: Operations Research & Optimization Research & Responsibilities Formulate and solve optimization problems including: Linear Programming (LP), Mixed-Integer Programming (MIP) Multi-objective optimization Scheduling, routing, allocation, and resource optimization Develop efficient algorithms and heuristics for complex decision problems Build simulation models and decision-support systems Apply optimization techniques to real-world operational, financial, and AI-driven systems What We’re Looking For Strong background in operations research, optimization, or applied mathematics Experience with tools such as Gurobi, CPLEX, OR-Tools, SCIP , or similar Deep understanding of mathematical modeling, algorithms, and computational complexity What Success Looks Like Continuous innovation through the adoption of frontier AI research Strong influence on data-driven decision-making across the organization A visible research presence via academic partnerships and publications Tangible impact across: Lending : reduced credit risk, improved approval rates, optimized pricing, enhanced fraud detection Marketing & Customer Protection : improved acquisition and retention, personalization, fraud prevention, increased customer lifetime value What You Bring Bachelor’s or Master’s degree in a quantitative field (Statistics, Mathematics, Computer Science, or similar) 4+ years of experience in AI, ML, data science, or applied research Proven track record of delivering impactful research-driven solutions Strong analytical thinking and problem-solving skills, with the ability to challenge conventional approaches while operating within regulatory and responsible AI constraints Research output (conference papers, workshops, pre-prints) is a strong advantage Master’s degree preferred; PhD is a strong differentiator Why Maya? At Maya, research doesn’t live in isolation. Your work will move from paper to production , shaping how millions of users experience financial services—responsibly, at scale. If you’re excited about doing serious AI research with real-world impact , we’d love to hear from you.
Maya
