Jakarta
Rp10 jt – Rp11 jt9 hari lalu
About OTA Indonesia (OTAZEN)
Founded in the early nineties, OTAZEN has grown into a world-class leader in the furniture manufacturing and logistics industry, exporting high-quality products across five continents. We cater to diverse sectors, including luxury hotels, domestic markets, and large-scale commercial contracts.
Operating out of our own advanced, independent production facilities equipped with cutting-edge woodworking technology, we pride ourselves on being completely self-sufficient and independent from external manufacturers. Our production processes adhere strictly to European quality standards and global sustainability initiatives, backed by annual FSC, COC, and SVLK certifications. At OTAZEN, we are our own most demanding customer, constantly creating and implementing global, innovative solutions to accelerate our business and support our international clients.
during the first 6–12 months. You will be responsible for getting your hands dirty—writing code, building data pipelines, and deploying production-ready AI solutions to optimize our manufacturing, supply chain, and enterprise workflows. As your solutions scale and drive measurable business impact, you will have the full authority to design the hiring roadmap, manage the budget, and build your own Data Science and AI team from the ground up.
Key Responsibilities
Architect, build, and deploy the company’s very first production-grade AI models, RAG systems, and data pipelines from scratch.
Collaborate directly with the executive team (C-Level) to translate manufacturing, logistics, and business challenges into scalable AI solutions (e.g., supply chain optimization, predictive maintenance, automated contract analysis, or internal knowledge management).
Explore and implement advanced Generative AI frameworks, including Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Agentic Workflows, alongside traditional Machine Learning models.
Establish robust MLOps practices using cloud infrastructure to ensure all deployed models are cost-effective, secure, low-latency, and highly reliable.
Define technical hiring criteria, conduct technical interviews, and gradually build a high-performing team of Data Scientists, AI Engineers, and Data Engineers as the division expands.
Act as the primary communicator between complex technical architectures and business outcomes, presenting milestones to non-technical stakeholders clearly.
Requirements & Qualifications
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