Top Machine Learning Jobs in the Philippines

Architects, develops, deploys, and maintains enterprise AI/ML solutions using NLP, OCR, RAG, and cloud-native platforms. The role modernizes fax and telephony workflows, mentors engineers, collaborates with product and development teams, solves complex problems, and ensures secure, scalable delivery. Responsibilities include model training, deployment, monitoring, MLOps/LLMOps practices, production support, and designing AI-driven automation.

Support mortgage servicing rights valuation and risk by designing, building, and delivering data-driven tools and analyses. Own end-to-end projects, manage data access and governance, develop Python utilities, implement analytical tooling into a proprietary platform, and communicate decision-ready insights to modelers and stakeholders.

Execute and reconcile daily trading activities from order entry through settlement, resolve discrepancies, prepare management reports, and ensure regulatory and policy compliance. The role drives automation, continuous improvement, stakeholder communication, and operational efficiency across trading services. It also supports strategic discussions, manages projects, and mentors junior team members while maintaining knowledge of financial markets and trading systems.

Lead payment lifecycle operations, including daily processing, reconciliations, investigations, exception management, and performance tracking. Resolve control and production breaks, manage operational risk, support fraud prevention, and escalate threats or delays. Partner with stakeholders on automation, process improvements, and client experience enhancements while translating business priorities into execution plans and measurable outcomes.

Leads franchise finance operations, FP&A, budgeting, forecasting, financial reporting, valuation modeling, fiscal controls, and business performance analysis. Partners with stakeholders on investment and productivity decisions, drives finance workflow automation, and develops multidimensional data models and analytics solutions. Requires finance expertise, data modeling and visualization experience, project and change management skills, and the ability to synthesize complex data for strategic decision-making.

Reviews financial services regulations and exchange rulebooks, assesses regulatory changes, and maintains auditable review records. Validates machine-learning topic classifications, provides labelled feedback, and helps maintain regulatory taxonomies. Compares platform rulebooks with authoritative sources to identify structural errors, missing provisions, duplication, and versioning issues. Performs quality assurance against development requirements and collaborates with product, engineering, and software teams to process new regulations and improve the service.

Develop and maintain complex data pipelines, APIs, statistical models, and advanced analytics solutions for commercial insurance and risk consulting. Use Python, PySpark, SQL, Databricks, AI, machine learning, and predictive modeling to produce data-backed consulting outputs and support new product development. The role also involves researching client risk areas, preparing recommendations, and consulting with senior colleagues on financial and statistical analyses.

Lead product vision and discovery for a genomics-driven diagnostic and personalization platform. Validate hypotheses with patients, clinicians, and partners; translate research into product specs; coordinate labs and data providers; partner with engineers and researchers to build AI prototypes; shape data, regulatory, and GTM strategy while making core product and architectural decisions.

Build core components of a diagnostic and personalization platform: backend data pipelines, frontends, services for genomic data ingestion, ML model integration, APIs, and cloud infrastructure. Collaborate with product and ML teams, iterate on prototypes and MVPs, and make architectural decisions supporting scalability and reliability.

Deploy and integrate AutoScience into customers’ machine learning infrastructure. Responsibilities include understanding ML systems, writing production Python, debugging distributed systems and pipelines, translating modeling problems into experiment environments, and owning deployments through production model improvements while collaborating with customers, researchers, and engineers.

Write technically accurate case studies, articles, product explainers, launch materials, and social content for AI engineers, researchers, and technical leaders. Interview customers, partners, and internal experts; learn HUD’s platform and workflows; explain technical products and research clearly; support founder communications; manage content from ideation through publication; and improve content using reader and go-to-market feedback.

Develop and support scalable full-stack business applications across the software development lifecycle. Responsibilities include building front-end interfaces, back-end services, APIs, databases, integrations, and Power Platform solutions; writing tested and secure code; troubleshooting; participating in code reviews; and applying CI/CD and DevSecOps practices. The role collaborates with cross-functional teams on digital transformation, prototyping, technical investigations, and continuous improvement.

Supports sales-force effectiveness through data cleaning, access governance, KPI reporting, performance trend analysis, and migration from Excel tracking to Power BI dashboards. The role also provides user support, onboarding and training assistance, documentation, process standardization, and continuous improvement across regional sales entities.

Own end-to-end campaign execution for assigned accounts, including setup, QA, launch, pacing, monitoring, optimization, and testing. Analyze campaign performance, identify anomalies and root causes, recommend improvements, communicate risks to managers and Customer Success, respond to alerts, document experiments, collaborate with Product, and mentor junior analysts.

Own end-to-end digital advertising campaign execution, including setup, QA, launch, pacing, optimization, testing, and daily performance monitoring. Analyze metrics such as pacing, fraud, creative performance, and delivery health; respond to alerts and inquiries within SLAs; document experiments; communicate campaign risks and updates; participate in on-call rotations; and support peer analysts. The role requires analytical skills, SQL/Python/R proficiency, and strong attention to detail.

Develop and maintain complex data pipelines, APIs, statistical models, and advanced analytics solutions for commercial insurance and risk consulting. Use Python, PySpark, SQL, Databricks, AI, machine learning, predictive modeling, and NLP to produce data-backed consulting insights and support new product development. The role also involves risk research, client-oriented solution development, and collaboration with senior stakeholders.

Support SOX testing and risk-based audits across Manulife’s global financial services operations. Perform control walkthroughs, design and operating effectiveness testing, identify root causes, communicate findings, validate issue closures, and apply data analytics to improve audit efficiency. The role requires collaboration across multicultural teams and adherence to internal audit methodology and IIA Standards, with opportunities to use GRC tools, machine learning, and Python.

Leads data projects, collects and governs data, develops pipelines, performs advanced statistical analysis, and creates predictive models, dashboards, and reports. Presents actionable insights to technical and non-technical stakeholders, provides strategic data advice, delivers data literacy training, improves analytics processes, and mentors junior team members. The role is onsite in Taguig, Philippines.

Performs portfolio accounting and investment administration activities, including securities settlement, foreign exchange, reconciliations, investment accounting, and fund reporting. Requires accurate analysis, reporting, problem solving, teamwork, and deadline management. The role is hybrid in Quezon City with a mid-shift schedule.

Collects, processes, and analyzes large datasets to identify trends, insights, and opportunities that improve business performance. Develops KPI reports, dashboards, data models, algorithms, and visualizations; evaluates data integrity; automates reporting; and communicates findings to technical and non-technical stakeholders. Supports analytics, automation, AI, and machine learning initiatives while collaborating with cross-functional teams and senior leadership.

Lead expense-management tooling enhancements from requirements through implementation and post-launch support. Translate business needs into user stories, acceptance criteria, and process improvements while coordinating stakeholders, dependencies, risks, timelines, testing, training, and adoption. Develop KPIs and dashboards to monitor operational effectiveness, controls, data quality, and compliance. Identify automation opportunities, support governance, and improve workflow efficiency, reporting, user experience, and operational risk management.

Leads cost accounting and operations finance projects, including acquisition integration into ERP and manufacturing systems. Performs data validation, controls testing, troubleshooting, process improvement, change management, training, and executive reporting. Partners with finance, IT, and cross-functional teams in a global matrixed environment while applying automation, AI, and analytics to improve financial reporting, anomaly detection, and root-cause analysis.

Supports cybersecurity operations by collecting, analyzing, and interpreting data to identify risks, anomalies, and emerging threats. Executes defined processes, maintains operating procedures, recommends efficiency improvements, and contributes to automation and process optimization. The role requires strong analytical skills, attention to detail, communication abilities, and foundational knowledge of scripting, queries, networking, and cyber monitoring. It is hybrid in Quezon City and requires night-shift availability.

Develops bioinformatics algorithms and machine learning models to detect early-stage cancer from cell-free DNA and epigenomic data. Responsibilities include experimental design, clinical genomics analysis, statistical modeling, software tool evaluation, production-ready coding, and communicating findings to cross-functional teams. The role requires strong computational biology, statistical learning, programming, and genomics expertise, with opportunities to use deep learning, SQL, and AWS.

Lead research on improving AI agent training data and evaluations. Manage and mentor research engineers, define research direction, design rigorous experiments, validate data quality, diagnose reward and grading failures, and translate findings into scalable tools, workflows, and standards. Collaborate with engineers, domain experts, and vendors while communicating technical conclusions and tradeoffs clearly.