Top Machine Learning Jobs in the Philippines

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

The Research Engineer will drive cutting-edge research into product pipelines, focusing on optimizing machine learning systems and innovative data curation strategies.

Provides technical consulting for AML, sanctions screening, and third-party risk solutions across APAC. Leads RFPs, sales engagements, client implementations, API integrations, data pipelines, analytics, reporting, and risk decisioning initiatives. Advises customers on data architecture, modeling, transformation, and enrichment while serving as a technical SME and customer advocate. Partners with sales, product, and delivery teams, presents at industry events, and monitors regulatory, technology, and competitive developments.

Support development and delivery of risk and compliance technology capabilities: gather and document requirements, drive UAT, assess solution designs, manage technology initiatives, integrate systems, and support AI/analytics adoption to enhance operational risk monitoring and reporting.

Write and maintain end-to-end documentation for robotic intelligence software, including architecture, APIs/SDKs, deployment, maintenance, and troubleshooting. Collaborate with researchers and engineers to gather technical details, establish documentation standards and tooling, and tailor content for both expert developers and non-technical field operators.

Design and deploy AI-driven solutions, build automation workflows, analyze data, support innovation, and collaborate with teams to address business needs.

Develop, deploy, and optimize scalable machine learning solutions, including predictive, supervised, unsupervised, and deep learning models. Build data pipelines, production model-serving infrastructure, monitoring, retraining, and lifecycle processes. Ensure AI solutions meet quality, security, compliance, governance, and responsible AI standards. Research emerging technologies and collaborate with data scientists, engineers, product teams, and business stakeholders to deliver measurable business value.

Leads the architecture, development, optimization, deployment, and governance of enterprise-scale machine learning systems. Responsibilities include model lifecycle management, MLOps, data quality, feature engineering, monitoring, responsible AI, compliance, technical strategy, innovation initiatives, and mentoring engineering teams.

Develops and supports SAP BI and data integration solutions, including data acquisition, cleansing, ETL, modeling, testing, troubleshooting, reporting, and documentation. Supports global analytics projects, business reporting, incidents, and on-call operations. Evaluates data sources, designs relational and dimensional models, automates repetitive tasks, and collaborates with analysts, engineers, and international business teams.

The Junior Project Manager will lead AI-focused projects, ensuring timely delivery and effective collaboration across teams while managing risks and compliance.

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.

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.

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.

Responsible for driving adoption of the FICO Platform by educating clients on its capabilities, managing sales targets, and building strategic relationships with senior executives, particularly in financial institutions.

The role involves leading strategic client accounts, managing complex deal structures, and collaborating with internal teams to create tailored solutions. Responsibilities include business growth, client advocacy, and market leadership while maintaining relationships with senior stakeholders in financial institutions.

Architect and improve autonomous AI optimization algorithms for a marketing platform. Analyze A/B tests, integrate AI models, develop multi-touch attribution, expand advertising-channel capabilities, reduce inference costs and latency, incorporate customer feedback, and maintain reliable, continuously improving optimization loops.

Responsible for driving revenue by acquiring new B2B customers, conducting technical discovery calls, managing sales pipelines, and collaborating with global teams.

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.

Own data quality and root-cause analysis for prediction issues: detect anomalies, trace sources, fix processes, automate QA/reporting with Python and SQL, maintain dashboards, and partner with Data Science, Engineering, Product, and Commercial teams to improve prediction performance and customer-facing analytics.

Develop product positioning, messaging, and go-to-market strategy for Autoscience's AI research systems. Create sales enablement and customer-facing materials, conduct market and competitive research, collaborate with research, engineering, sales, and leadership, and communicate product value to customers, partners, and the AI community.

Develop and implement AI systems for automated research, collaborate on production-ready models, publish research, and stay updated on AI trends.

Manage privacy engineering initiatives by conducting assessments, developing compliance solutions, and integrating AI technologies, ensuring regulatory adherence and risk mitigation.

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.

Lead design and delivery of analytics, automation, and AI-enabled data solutions to improve operational efficiency across Asia Pacific. Build data pipelines, models, dashboards, desktop apps and Excel add-ins; advise stakeholders, manage projects, establish standards, and coach junior team members.