Top Machine Learning Jobs in Caloocan

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 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.

Analyze and improve AI-powered transaction monitoring systems for money laundering, fraud, sanctions, and terrorist financing detection. Review high-risk transactions, identify behavioral patterns, test and refine machine learning models, develop metrics and dashboards, conduct experiments and ad hoc analyses, and provide clear recommendations. Collaborate with compliance, legal, Identity & Trust, and operations teams while ensuring AML and sanctions regulatory adherence and a positive customer experience.

Reconcile securities holdings, cash balances, and transactions across investment portfolios. Investigate discrepancies, coordinate resolutions with custodians and stakeholders, review reconciliation outputs, maintain reporting and documentation, and support compliance, audits, process improvements, UAT, and system enhancements.

The Investor Services Senior Administrator executes tasks in the Investor Services Department, reviews transaction instructions, liaises with investors, and prepares reports and wire transfers. Requires strong analytical and communication skills.

Develop and deliver analytics solutions, statistical models, and AI-powered applications using large and complex datasets. Translate analysis into actionable business recommendations, collaborate with stakeholders, manage end-to-end analytics projects, and mentor junior data scientists. The role includes designing NLP and LLM solutions, applying machine learning techniques, using visualization tools, and supporting scalable analytics processes across customer lifecycle use cases.

Own the vision, strategy, roadmap, and lifecycle of a shared lending platform serving multiple products and markets. Define platform architecture principles, APIs, configuration capabilities, and build-versus-buy decisions. Lead real-time credit decisioning, risk and compliance integrations, data aggregation, IFRS9 reporting, and ML-assisted lending capabilities. Coordinate dependencies across lending products and collaborate with Credit Risk, Analytics, Engineering, Compliance, and country business teams.

Coordinates and expedites procurement commercial change orders from RFQ through completion. The role follows up with suppliers, validates documentation, tracks quotations and part numbers, escalates delays, maintains KPI dashboards and reports, and collaborates with procurement, engineering, category management, and other stakeholders. It also supports process improvement, automation, compliance, stakeholder meetings, supplier communications, and training for junior team members.

Lead and facilitate Six Sigma improvement projects across multiple business units, apply data-driven statistical problem solving, define performance metrics, present findings to senior leadership, deploy process trainings, manage idea programs, and support operational excellence for 200-400 FTEs.

Maintains and improves procurement item data and ERP attributes, including pricing, lead times, minimum order quantities, sourcing rules, costing, and buyer/planner assignments. Coordinates sourcing approvals, supplier communications, procurement system updates, and stakeholder activities. Tracks KPIs, ensures transaction accuracy, resolves sourcing issues, supports automation tools, and provides peer guidance. The role also reviews data quality, manages deadlines, identifies risks, and contributes to process improvement.

Leads SGS’s enterprise AI agenda for Finance, managing strategy, use-case prioritization, governance, cross-functional delivery, responsible AI controls, adoption, and value realization. The role coordinates Finance, IT, Data, Risk, Cybersecurity, Privacy, Legal, vendors, and implementation partners to deploy scalable AI solutions while tracking business outcomes, risks, budgets, controls, and user adoption globally.

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.

Leads technical presales activities for enterprise customers and channel partners across a regional territory. Identifies cybersecurity needs, designs and presents Sophos solutions, conducts demonstrations and proof-of-concepts, enables partners, supports account planning, and drives technical sales closure and revenue. Acts as a trusted cybersecurity advisor across endpoint, network, cloud, XDR, SIEM, and MDR solutions while building customer and partner relationships.

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.

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.

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.

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.