Top Machine Learning Jobs in the Philippines

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.

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.

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.

Develop, validate, debug, and optimize machine learning models, training pipelines, inference systems, and numerical implementations using Python. Build reproducible workflows, diagnose computational issues, create systematic tests, and improve memory usage, throughput, and performance. Review code and solutions, use coding agents in development, document technical findings, and deliver reliable work independently within project deadlines.

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.

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.

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.

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.

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.

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.

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.

Own the full enterprise sales cycle for AI-driven forecasting and optimization solutions, from pipeline generation through closing and customer partnership. Sell to senior executives across supply chain, manufacturing, CPG, retail, and logistics organizations. Build relationships, quantify ROI, manage complex multi-stakeholder deals, close six- and seven-figure contracts, maintain CRM accuracy, forecast reliably, and help shape the company’s sales playbook and go-to-market strategy.

Leads customer-facing applied AI engagements by understanding operational challenges, framing business problems, delivering technical demos, and building Python- and SQL-based prototypes. Supports enterprise sales cycles, evaluations, pilots, implementations, and customer deployments. Requires strong data science and machine learning knowledge, business intuition, project management, and the ability to communicate with technical and non-technical stakeholders.

Own client onboarding, configuration, adoption, troubleshooting, communications, retention, and expansion for B2B SaaS AI agent solutions. Provide technical guidance to nontechnical stakeholders, manage go-lives, collaborate with engineering on APIs and integrations, and support customers during US business hours. The role requires strong English and Spanish communication, independence, organization, and customer relationship management.

Own post-sale customer relationships for an AI Agents platform, including onboarding, configuration, adoption, troubleshooting, issue resolution, and go-live acceleration. Manage multiple B2B SaaS accounts, communicate progress, coordinate technical handoffs, monitor satisfaction and retention, and identify expansion opportunities. The role requires strong technical aptitude, customer relationship management, problem-solving, communication, and familiarity with AI, APIs, and technical workflows.

Perform legal data collection, evaluation, and annotation for AI-powered contract management platforms in Simplified Chinese. Analyze clauses, obligations, and terms in international business contracts; participate in onboarding, calibration, and quality reviews; and collaborate within secure client environments. Requires contract or legal expertise, strong legal interpretation and contract-review skills, and fluency in English and Simplified Chinese. Prior data annotation or machine learning evaluation experience is preferred.

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.

Develop predictive and prescriptive analytics, machine learning models, and data models for semiconductor manufacturing. Analyze production, quality, process, and equipment data to improve yield, productivity, and operational efficiency. Collaborate with manufacturing engineers and stakeholders, support smart manufacturing initiatives, and communicate insights to technical and business audiences.

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.

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.

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.