Top Machine Learning Jobs in Quezon City

Lead and scale a Manila-based, client-facing Data, Analytics, and AI practice across the deal lifecycle. Deliver AI/ML/GenAI solutions, manage mid-to-large analytics engagements, drive go-to-market and pre-sales, mentor junior staff, and ensure high-quality end-to-end delivery for M&A and transaction advisory work.

Lead and scale Manila-based Data, Analytics, and AI teams to deliver end-to-end AI/ML and GenAI solutions for transaction advisory. Drive go-to-market, client pursuits, delivery quality, mentorship, automation for due diligence, and cross-functional techno-functional collaboration across industries.

As a Senior Data Scientist at Feedzai, you will analyze client data, develop models, preprocess data, and collaborate with teams to enhance risk management solutions.

Design, build, and maintain backend APIs and services for a real-time supply chain visibility platform. Own system architecture, real-time event ingestion, data normalization, ML integration, monitoring, and production debugging while collaborating with Product and Data Science to deliver scalable, high-availability features.

Design and deploy AI/ML models and automation to improve procurement analytics, integrate data from ERP and BI tools, build dashboards, lead digital projects, and drive stakeholder adoption and training.

Support Internal Audit by designing and executing data analytics, building Power BI dashboards, performing SQL/Python-based ETL and analyses, preparing audit workpapers/reports, and communicating findings to global audit stakeholders to improve controls and processes.

The Data Scientist will develop analytics solutions, work with complex datasets, deliver insights, mentor junior staff, and collaborate with business teams.

Perform remote, part-time data tasks to improve AI in Tagalog: collect, evaluate, and annotate data; perform pairwise comparisons, counting, and object tagging across audio, video, images, and collected data. Requires native Tagalog and fluent English; AI/data experience preferred. Freelance, flexible schedule, immediate start, 10+ hours/week.

Develop and implement AI and machine learning strategies in healthcare, collaborate with teams, mentor engineers, and ensure code quality while driving innovative solutions.

Lead controls, governance, reporting and analytics for Global Investments Operations. Manage reconciliations, dashboards (PowerBI), data gathering/cleansing, root cause analysis, process improvements, compliance support and stakeholder coordination.

The Private Equity Supervisor at HedgeServ manages a team of accountants, ensures service consistency, oversees fund accounting, and develops client relationships while enhancing workflows and procedures.

Build, maintain, and improve programming solutions and AI/ML applications to automate workflows, analyze operational data, and optimize processes. Collaborate with cross-functional teams, maintain operational systems, and document technical procedures to support reliable, scalable operations.

This internship involves developing AI-driven solutions, testing features with LLMs, building prototypes, collaborating with engineers, and exploring AI capabilities.

Work with Product, Business, and Engineering to collect, clean, analyze data, build Python and SQL automation, contribute to internal analytics platforms, assist cloud deployments, and document technical solutions to support decision-making.

The Catastrophe Modeling Analyst quantifies risk, analyzes client exposure using models, applies machine learning techniques to datasets, and produces clear reports and dashboards.

Lead design, build, and deploy AI-driven automation and AI agents to transform finance operations. Partner with finance teams to redesign processes, improve reporting, enhance data governance, and drive adoption through change management, training, and ongoing capability building.

Manage overall NAV calculation for credit-based funds, client relationships, fund accounting team, and ensure timely delivery of NAV calculations while supporting audits and training.

Responsible for overseeing fund accounting tasks, including NAV calculations, reconciliations, and mentoring team members while ensuring compliance with procedures.

Lead design, implementation, and optimization of fraud detection rules and ML models. Analyze large datasets for emerging fraud, monitor KPIs, manage vendor/tool integration, lead incident investigations, and ensure quality assurance and documentation of fraud strategies.

Early-career role analyzing PB-scale on-chain, transactional and customer data. Perform data engineering, ETL, querying, build visualizations and ML models, translate insights for teams, manage reporting environment, secure confidential data, and troubleshoot reports/databases.

Lead design and management of search and content recommendation services and models. Build personalized recommender systems using ML/AI, define success metrics with product and business teams, drive core module development, and translate PB-scale data insights into measurable product impact.

Design, back-test and implement pricing, risk management, and agency trading strategies; collaborate with developers to integrate models into the trading platform; participate in product ideation, modeling, parameter tuning, and risk evaluation.

Design, develop, and manage large-scale search and content recommendation systems. Apply ML-based personalization to improve content matching and distribution. Lead core recommendation module development, define success metrics, and collaborate with content, product, and business teams to drive AI product upgrades and better user and business outcomes.

Early-career Performance Engineer in the Binance Accelerator Program. Perform hands-on performance testing and tuning, design AI-powered test strategies using LLMs and ML, build AI-driven anomaly detection and bottleneck analysis tools, research new AI technologies, and improve reliability of large-scale distributed systems.

Design, build, and manage large-scale search and content recommendation systems using machine learning and personalization techniques. Collaborate with content, product, and business teams to define success metrics, drive AI product improvements, and maximize content value and user impact.