Top Machine Learning Jobs in Davao City

Develop and execute B2B SaaS marketing strategies using HubSpot, AI-powered automation, analytics, and data science. Manage marketing workflows, campaigns, email programs, website optimization, attribution, A/B testing, and dashboards to improve pipeline, conversions, and revenue. Lead cross-functional marketing operations projects, maintain data quality, document repeatable processes, and align Marketing, Sales, and Customer Service teams.

Designs, develops, and maintains financial business intelligence, data integration, dashboards, data warehouses, ETL processes, and SQL-based reporting solutions. Partners with Finance, Accounting, IT, and business stakeholders to translate reporting needs into reliable technical solutions, troubleshoot data issues, support management reporting, and improve data quality. The role also drives automation, standardization, continuous improvement, and analytics innovation across the Americas Controllership organization.

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.

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.

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.

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.

Build and maintain mission-critical wealth management systems for SMB clients. Design data pipelines, ETL/ELT processes, data models, warehouses, analytics, and reporting solutions using AWS, Snowflake, Mage AI, and other big data tools. Collaborate with data scientists and analysts on predictive models, statistical analyses, and machine learning algorithms. Develop software with Next.js and Python while working closely with the team and clients on financial-domain challenges.

Build privacy and anonymization systems that detect and transform PII, credentials, secrets, and other sensitive information in data used for AI training. Develop detection methods combining rules, statistical models, classifiers, and LLMs; create production data-processing pipelines; evaluate privacy risk and retained utility; and ensure robustness against schema drift, unusual formats, leakage, and adversarial re-identification.

Own the end-to-end lifecycle of complex digital products, from requirements definition and feature prioritization through delivery and continuous optimization. Collaborate with engineering, design, marketing, and business stakeholders; analyze markets, competitors, customer feedback, and product metrics; facilitate requirements workshops; and translate business needs into scalable technical solutions. The role focuses on fintech, payments, banking, loyalty, rewards, e-commerce, and AI-powered personalization platforms.

Own and improve the Command|Alert alerting platform, including rule evaluation, anomaly detection, event correlation, reliable Kafka and OpenSearch pipelines, and downstream notifications. Convert security and network telemetry into usable topologies and dependency maps, support LLM-based alert generation, resolve production issues, lead reliability improvements, deliver independent projects, and mentor engineers while shaping technical direction.

Bridges business needs and AI solutions by gathering requirements, assessing AI and automation opportunities, developing business cases, supporting solution design and delivery, facilitating stakeholder collaboration, assisting testing and implementation, and tracking project outcomes, benefits, reports, and continuous improvement initiatives.

Leads operational oversight for AI-powered products and platforms, monitoring performance, developing dashboards, analyzing business outcomes, and driving process improvement. The role supports AI governance, risk management, compliance, operational standards, forecasting, and scalable operating models. It also partners with engineering, product, and business stakeholders to deliver operational excellence and present strategic recommendations.

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 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.

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.

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 and scale customer-facing and internal web applications for an AI-powered eCommerce customer service platform. Develop and enhance AI agents, integrate eCommerce platforms, apply privacy and security practices, and help shape the product’s technical direction. As the founding technology team member, the role offers significant ownership, equity, and potential progression into technical leadership.

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.

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.