Top Machine Learning Jobs in Caloocan

Perform remote, part-time data tasks to improve AI in Tagalog: collect, evaluate, and annotate data; perform pairwise comparisons, counting, and object tagging across audio, video, images, and collected data. Requires native Tagalog and fluent English; AI/data experience preferred. Freelance, flexible schedule, immediate start, 10+ hours/week.

The Data Scientist will develop analytics solutions, work with complex datasets, deliver insights, mentor junior staff, and collaborate with business teams.

Manage delivery of multiple concurrent software, data, automation, and AI programs from intake to adoption. Coordinate distributed engineers and analysts across time zones, run delivery cadence, align business partners, maintain portfolio governance, surface risks with mitigation, and continuously improve delivery processes focused on shipped outcomes.

Lead delivery of multiple concurrent software, data, and AI programs from intake to deployment. Coordinate distributed engineers and analysts, run delivery cadence, align business partners, manage risks and dependencies, and improve portfolio governance and PM practices to ensure adoption and shipped outcomes.

Design, prototype, and deploy production-ready machine learning and generative AI solutions and agentic workflows. Own end-to-end model delivery, data and feature engineering, evaluation, deployment, monitoring, retraining, and governance. Collaborate with product, engineering, and risk stakeholders and contribute reusable patterns and services to accelerate adoption and ensure responsible AI practices.

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.

Analyze large-scale on-chain data to detect anomalous transactions, develop detection mechanisms and risk monitoring frameworks, apply supervised and unsupervised ML, identify malicious accounts via community-discovery algorithms, and design integrated on-chain/off-chain prevention and control systems.

Lead strategy and execution for fraud risk management across the platform. Develop detection and prevention frameworks, optimize transaction screening, partner with Compliance, Data Science, Engineering and Product, oversee KPIs and vendor costs, lead a risk strategy team, and pilot AI/LLM-driven tools to enhance detection while enabling business growth and regulatory alignment.

Manage overall NAV calculation for credit-based funds, client relationships, fund accounting team, and ensure timely delivery of NAV calculations while supporting audits and training.

Responsible for overseeing fund accounting tasks, including NAV calculations, reconciliations, and mentoring team members while ensuring compliance with procedures.

Own data quality and root-cause analysis for prediction issues: detect anomalies, trace sources, fix processes, automate QA/reporting with Python and SQL, maintain dashboards, and partner with Data Science, Engineering, Product, and Commercial teams to improve prediction performance and customer-facing analytics.

Lead engineering projects, automation and digitization, new product qualification, and machine/process reliability. Manage budgets, timelines, root-cause troubleshooting, maintenance strategy, and integration of advanced manufacturing technologies. Mentor and develop engineering team, ensure safety and compliance, and coordinate with regional/global stakeholders to drive productivity and operational excellence.

Design and deploy AI/ML models and automation to improve procurement analytics, integrate data from ERP and BI tools, build dashboards, lead digital projects, and drive stakeholder adoption and training.

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.

Lead a team of Business Insights Analysts to analyze large datasets, define operational metrics and dashboards, surface actionable insights, drive process improvements, partner with data visualization teams, and influence cross-functional stakeholders to optimize performance and reduce costs.