Top Artificial Intelligence Jobs in Caloocan

The Demand Planner oversees sales forecasting, collaborates with teams to analyze trends, manage inventory, and improve forecast accuracy.

Manage daily sales operations, coach team members, monitor performance, shape sales strategy, enhance customer satisfaction, and drive results through data insights.

As a Sales Graduate, you will understand customer needs, design solutions, support account teams, and advance sales opportunities while enhancing your professional skills.

Develop, test, deploy, and maintain production-grade AI/ML models and LLM-powered applications. Participate across the AI lifecycle, implement cloud/IaC solutions, contribute to reusable platforms, collaborate with cross-functional teams, and troubleshoot production issues while learning from senior engineers.

The position offers IT technical support, focusing on aiding users with technology-related issues and ensuring seamless business operations within the company.

The Senior AI ML Engineer designs and develops full-stack applications, integrates AI/ML models, manages cloud deployments, and ensures secure data access.

The Research Analyst will handle content onboarding, client requests through RPDs, perform QA checks, and utilize analytical and problem-solving skills within the finance industry.

The role involves building client relationships, educating on the FICO Platform, managing software solutions sales, and achieving sales targets.

Lead end-to-end AI client implementations, build and maintain AI automation workflows (n8n), design and optimize prompts and LLM integrations, manage backend API/database integrations, mentor team members, and own delivery standards, project timelines, and client outcomes.

Develop and edit videos and digital content using AI tools, build landing pages, package courses, and maintain production operations and reporting.

As a Lead AI Architect, you will design and deliver enterprise-grade AI/ML solutions, mentor engineers, establish best practices, and ensure production-ready systems.

Design, develop, and deploy AI solutions on Microsoft Azure (ML, Cognitive Services, OpenAI). Build/train models (NLP, vision), integrate conversational and prebuilt AI capabilities, apply Responsible AI, monitor with Azure tools, and optimize MLOps pipelines.

Design, build, and deploy multi-agent, agentic AI systems using modern LLMs and frameworks. Implement tool/API integrations, agent-to-agent communication, and reliable CI/CD pipelines while ensuring governance, security, and compliance. Collaborate with cross-functional teams on architecture, code reviews, and production-grade deployments.

Design and deploy practical AI systems and agentic workflows to automate fintech processes; write Python/SQL to extract insights; orchestrate data and workflows (n8n); own projects and upskill teammates on AI tooling.

Lead AI PoC efforts across business units: identify and prioritize use cases, define scope and success metrics, coordinate execution with data/IT/vendors, validate business impact, and transition validated solutions into production with governance and stakeholder alignment.

Manage social media strategies across multiple brands, produce AI-enhanced content, engage communities, and deliver performance analytics.

As a Senior AI Engineer, you'll design and deliver scalable AI solutions, lead LLM integration, and mentor engineers while ensuring performance, reliability, and quality compliance.

Design and deploy practical AI systems for the FinTech team, write Python/SQL to extract insights, build agentic AI workflows to automate financial processes, orchestrate data and connect systems with tools like n8n, and upskill teammates on AI tools.

The ML/AI Engineer will design, develop, and implement machine learning models and AI solutions, collaborating with software engineers and cross-functional teams.

The AI Software Engineer will design, develop, and maintain AI software solutions for industrial automation, ensuring backend and frontend integration, and contributing to CI/CD processes. Collaboration with global teams and maintaining documentation is key to aligning technical solutions with business goals.

Drive end-to-end design and development of AI solutions, focusing on performance, reliability, and technical leadership in AI engineering.

The Engineer II will develop, maintain, and enhance RPA solutions while collaborating with teams to streamline business operations.

The AI Application Developer designs and develops AI solutions using LLMs and RAG. Responsibilities include optimizing model performance, implementing decision logic, and building scalable applications.

The Recruitment Assistant will source qualified candidates on LinkedIn, utilize AI tools for resume evaluation, and draft personalized outreach messages.

The role involves researching and writing various content types related to technology and SaaS, focusing on user-friendly copy that aligns with clients' voice and style.