Top Machine Learning Jobs in the Philippines

Leads business analysis for AI and automation initiatives by identifying adoption opportunities, defining requirements, developing business cases, facilitating stakeholder alignment, and supporting solution design and delivery. Monitors outcomes, value realization, governance, compliance, change management, and continuous improvement while mentoring junior analysts. Translates business objectives into technical requirements and advises executives and technical teams throughout AI transformation programs.

The AI Security Analyst will assess and mitigate risks across AI systems, machine learning platforms, and Generative AI applications. Responsibilities include threat modeling, vulnerability assessment, security monitoring, incident response, root cause analysis, access control, governance, compliance, policy development, and secure AI design reviews. The role partners with engineering, infrastructure, security, governance, and business teams to improve AI security capabilities and promote responsible AI adoption.

Owns AI product backlogs, priorities, user stories, acceptance criteria, and requirements. Translates business needs into technical solutions while coordinating stakeholders, AI engineers, product managers, and delivery teams. Supports Agile planning, product releases, adoption monitoring, continuous improvement, AI innovation, and responsible AI practices. Facilitates workshops, manages expectations, and contributes to AI product strategy and value realization.

Leads the strategy, roadmap, delivery, and continuous improvement of AI-powered products. Defines product vision, requirements, priorities, metrics, and success criteria while collaborating with executives, engineering, AI, data science, and business teams. Oversees product launches, adoption, performance optimization, stakeholder communication, and responsible AI governance. Requires strong product management, analytical, commercial, Agile, executive communication, and cross-functional leadership skills.

Supports responsible AI governance through framework development, risk and impact assessments, fairness and transparency reviews, regulatory compliance, documentation, stakeholder advisory, training, and continuous improvement. The role collaborates with technical, legal, compliance, risk, and business teams to promote ethical, accountable, and trustworthy AI adoption.

Supports enterprise AI governance by developing policies, maintaining control frameworks, assessing AI risks, monitoring regulatory compliance, and reporting governance metrics. Collaborates with legal, compliance, security, AI, and business stakeholders to promote responsible AI practices. The role also researches emerging regulations, supports audits, documents findings, and recommends improvements to governance processes.

Own the strategy, roadmap, development, delivery, and continuous improvement of AI-powered products. Translate business objectives and customer needs into product requirements, success metrics, and business cases. Partner with engineering, AI, operations, leadership, and customers to manage product lifecycles, adoption, ROI, governance, compliance, and responsible AI practices.

Supports the day-to-day operation, monitoring, reporting, governance, and continuous improvement of AI-powered platforms. Analyzes performance metrics, identifies operational issues and optimization opportunities, develops dashboards and reports, maintains procedures and documentation, and coordinates issue resolution across AI engineers, product teams, operations leaders, and business stakeholders. The role also supports AI adoption, compliance, risk mitigation, and operational standards.

Tests and validates AI-powered products, machine learning models, and Generative AI applications. Designs test strategies, executes functional, regression, and acceptance testing, validates model outputs, identifies defects, analyzes quality metrics, documents results, and supports compliance and release readiness. Collaborates with AI engineers, product managers, and business teams while improving AI testing methodologies and quality frameworks.

Build AI-enabled tools that solve strategic business problems, improve operations through intelligent automation, and accelerate decision-making with machine learning. Design and implement solutions using ML models, large language models, and data science pipelines. Work with cloud technologies, modern development tools, and deep learning frameworks while continuously developing expertise in machine learning.

Designs and maintains scalable microservices, APIs, GenAI pipelines, MCP servers, and ML models for enterprise AI capabilities. Integrates LLMs from multiple providers, builds agentic workflows, and develops evaluation and retraining processes. The role also ensures AI workloads meet security, reliability, scalability, and performance standards in AWS and Kubernetes environments, while collaborating with platform, ML engineering, and data science teams.

Leads the strategy, development, and delivery of AI, machine learning, and generative AI solutions across healthcare domains. Responsibilities include designing scalable software, integrating LLMs and agentic AI, maintaining code quality and production operations, collaborating with stakeholders, mentoring engineers, and leading AI/ML teams. The role requires expertise in modern ML frameworks, cloud platforms, DevOps, CI/CD, NLP, model evaluation, prompt engineering, and production-grade AI applications.

Analyzes structured and unstructured data, develops and deploys predictive and machine learning models, designs experiments, creates dashboards, ensures data quality, and communicates insights to technical and business stakeholders. Senior-level candidates may lead analytical initiatives, mentor junior staff, and influence strategic decisions.

Analyze catastrophe risk for reinsurance contracts using third-party catastrophe models, validate model outputs, price submissions, and create exposure reports. Apply machine-learning methods to clean and align large datasets and generate decision-ready insights. Develop concise reports, dashboards, and reproducible Python or R notebooks for nontechnical stakeholders. The role requires strong analytical, communication, organizational, and attention-to-detail skills, with flexibility for extended hours during peak periods.

Own an AI-native stockbroking product vertical end-to-end, including strategy, metrics, roadmap, technical design, delivery, and launch. Partner with engineering on APIs, data flows, ledgering, reconciliation, security, scalability, and failure handling. Incorporate KYC, transaction monitoring, limits, privacy, licensing, regulatory approvals, and third-party financial rails. Apply AI with appropriate evaluation, safeguards, human oversight, and reliability controls while aligning engineering, design, compliance, operations, treasury, and finance.

Manage employee relations and HR operations for the Manila office, including performance improvement plans, disciplinary and grievance processes, absence management, labor-law compliance, exit interviews, manager support, training, onboarding, offboarding, benefits administration, and HR projects. Partner with managers and senior leaders as a trusted people advisor while supporting a fast-paced, hybrid global organization and working European hours.

Recruit, onboard, activate, and grow managed service provider partners across assigned markets. Own recurring revenue growth, product adoption, cross-sell, partner tier progression, and consumption-based sales. Deliver partner onboarding, business reviews, certifications, and sales enablement while managing high-volume pipelines, forecasting, deal registration, distributor alignment, and presales collaboration in Salesforce.

Develop and deploy AI and machine learning solutions that improve internal efficiency and create customer value. Responsibilities include integrating data from diverse sources, transitioning prototypes into production, integrating models with existing systems, optimizing performance, maintaining code quality, improving business processes, and supporting organizational adoption through training and change management.

Develops data-driven business insights through statistical analysis, SQL querying, dashboards, reporting strategy, and executive storytelling. Translates analytical findings into actionable recommendations, oversees reporting roadmaps, partners with visualization and engineering teams, and identifies business risks and opportunities. The role is fully onsite on a night shift in Imus, Cavite or Ortigas.

This 12-week engineering internship supports P&G technical centers and manufacturing sites. Interns contribute to automation and controls, mechanical design, packaging, manufacturing process development, instrumentation, robotics, and environmental or civil engineering projects. Responsibilities include technical analysis, prototyping, process optimization, equipment and control-system development, validation, supplier collaboration, and sustainability initiatives. Interns receive mentorship, training, hands-on project ownership, and exposure to advanced manufacturing and Industry 4.0 technologies.

Lead product marketing strategy for an AI infrastructure platform, owning positioning, category narrative, product launches, competitive intelligence, sales enablement, analyst relations, and customer insights. Translate technical products into narratives for developers and enterprise buyers, improve competitive win rates and pipeline conversion, and build a scalable PMM team.

Design, implement and support web and mobile (Android/iOS/hybrid) software solutions as part of a Scrum team. Attend client meetings, communicate progress, learn deployment processes, and travel for on-site assignments and training.

Develop and maintain Power Platform-based BI solutions and automations, perform ETL and data cleansing, build Power BI dashboards and predictive risk models, integrate AI/ML into reporting, and support cybersecurity, IT, and finance data collection and visualization for senior leadership and operational teams.

Lead NAV operations and fund administration activities, ensuring accurate NAV calculation, regulatory compliance, client service, team leadership, and technology-enabled process improvement.

Senior technical leader providing high-level AI strategy, architecture direction, and long-term systems design. Delivers strategic artifacts (architecture reviews, AI integration strategies, roadmaps), advises executives, collaborates with product and engineering teams, and mentors technical leaders to improve scalability, resilience, and governance across platforms.