Top Machine Learning Jobs in Manila

Design, develop, and manage large-scale search and content recommendation systems. Apply ML-based personalization to improve content matching and distribution. Lead core recommendation module development, define success metrics, and collaborate with content, product, and business teams to drive AI product upgrades and better user and business outcomes.

Design, build, and manage large-scale search and content recommendation systems using machine learning and personalization techniques. Collaborate with content, product, and business teams to define success metrics, drive AI product improvements, and maximize content value and user impact.

Early-career Performance Engineer in the Binance Accelerator Program. Perform hands-on performance testing and tuning, design AI-powered test strategies using LLMs and ML, build AI-driven anomaly detection and bottleneck analysis tools, research new AI technologies, and improve reliability of large-scale distributed systems.

Design, back-test and implement pricing, risk management, and agency trading strategies; collaborate with developers to integrate models into the trading platform; participate in product ideation, modeling, parameter tuning, and risk evaluation.

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, build, and deploy AI-driven automation and AI agents to transform finance operations. Partner with finance teams to redesign processes, improve reporting, enhance data governance, and drive adoption through change management, training, and ongoing capability building.

Design, architect, and deliver secure AI-powered low-code/no-code automations across Salesforce, EDI, SAP ERP, and order-to-cash systems using Power Platform and advanced AI patterns (RAG, agent orchestration, prompt engineering). Partner with finance, sales ops, and IT to implement, monitor, and govern solutions, measure ROI, and support production deployments and incident remediation.

Lead item data attribution and ERP procurement parameter maintenance, resolve complex sourcing and MDM issues, manage Snow ticket and BOM updates, generate reports and KPI dashboards, deploy automation (RPA/ML/More4Apps), mentor peers, and drive process improvements to ensure data integrity and procurement efficiency.

Early-career role analyzing PB-scale on-chain, transactional and customer data. Perform data engineering, ETL, querying, build visualizations and ML models, translate insights for teams, manage reporting environment, secure confidential data, and troubleshoot reports/databases.

Analyze PB-scale trading, transactional, operational and customer data; build visualizations, ML models and experiments; translate findings into actionable recommendations for trading, operations, product and executives in a fast-paced environment.

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.

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.

The Sales Manager will drive revenue growth and expand market share in the Philippines through strategic sales initiatives, client relationship building, and leading sales cycles.

Design, build, and deploy scalable ML models and pipelines from research to production. Own feature engineering, model tuning, real-time prediction, MLOps automation, monitoring, and lifecycle management to solve visibility, forecasting, and freight audit problems.

Lead end-to-end ML lifecycle: research SOTA architectures, fine-tune foundation models, design data pipelines, deploy models with MLOps (Docker/Kubernetes/CI-CD), build APIs, implement model governance, and collaborate within cross-functional agile squads.

Own and grow BioCatch accounts in the Philippines (primarily banking/financial services). Build strategic account plans, prospect and close new business, upsell and cross-sell, collaborate with APAC commercial teams, manage pipeline/forecasting, represent BioCatch at events, and drive customer satisfaction and technology adoption.

Own end-to-end ML model lifecycle from EDA and feature engineering to production deployment and monitoring. Collaborate with cross-functional teams to identify modeling opportunities, evaluate performance and business impact, integrate new data sources, and ensure scalable, observable production systems.

Design, implement, and optimize production-ready machine learning models and pipelines. Collaborate with data, software, and product teams to integrate ML solutions. Perform data preprocessing, feature engineering, EDA, training, validation, deployment, and monitoring. Maintain environment setup, scalable APIs, and database architecture. Document work and stay current with ML research and best practices.

Design, automate, and manage end-to-end ML pipelines and scalable infrastructure on Azure. Build CI/CD with GitHub Actions, containerize models with Docker and AKS, monitor model lifecycle and data drift, implement cost controls, and collaborate with data science, DevOps, and IT to deploy resilient, production-grade ML solutions.