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Windranger Labs

Technical AI Researcher

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Singapore
Singapore

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Mantle is building the largest sustainable hub for on-chain finance. Through its core products — Mantle Network, mETH Protocol, and FBTC — Mantle is building banking for the next generation by leveraging the transformative power of blockchain. Anchored by the Mantle Treasury, the largest community-owned treasury in the ecosystem, Mantle ensures robust liquidity and financial stability. With over $4.3 billion in assets, it actively funds core product development and fosters the growth of asset partners, such as Agora AUSD, Ethena USDe, Ondo USDY, and EigenLayer restaking, enhancing sustainable yield, deep liquidity, and financial utility on the Mantle Network.
MantleX is seeking a mid-level AI Engineer to join our multidisciplinary team, helping to define and execute our AI strategy, build early-stage solutions, and showcase the transformative potential of AI across the organization. You’ll work with a range of technologies—including agentic frameworks, chatbots, and ML models—to drive innovation, streamline processes, and solve real business challenges. In this role, you will manage AI-related processes and R&D initiatives in alignment with MantleX’s broader AI roadmap, identifying and addressing business needs through AI-driven solutions that deliver measurable value. Additionally, you’ll analyze, explain, and deploy AI/ML solutions with a strong emphasis on maintaining high ethical and responsible AI practices.


Responsibilities

  • Design, build, optimize, and deploy machine learning models tailored to specific business challenges.

  • Collaborate with cross-functional teams to define objectives and integrate models into production systems.

  • Train and fine-tune models using advanced algorithms, ensuring optimal performance through techniques like cross-validation and hyperparameter optimization.

  • Conduct rigorous testing, prototyping, and performance assessments before production deployment.

  • Work closely with software engineers and DevOps to implement APIs and integrate models into existing applications for real-time decision-making.

  • Articulate solution architecture and document lessons learned for future reference.

  • Continuously track model performance, address anomalies, and incorporate user feedback for ongoing improvement.

  • Establish robust monitoring and alerting systems to maintain high standards of availability and reliability.

  • Conduct exploratory data analysis and create dashboards or visualizations to communicate insights effectively.

  • Translate complex data trends into actionable recommendations for stakeholders.

  • Stay informed about emerging AI/ML technologies, frameworks, and best practices.

  • Recommend new methodologies, tools, or processes that can enhance workflow efficiency or model performance.


Required Skills and Qualifications

  • Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field

  • Demonstrated passion for AI, with a proactive and adaptable mindset

  • Strong communication skills and ability to translate technical concepts to non-technical stakeholders

  • 1–2 years of experience applying AI solutions to real-world use cases

  • Knowledge of agentic frameworks, launchpads, and relevant AI/ML use cases

  • Proficiency in machine learning, deep learning, and frameworks like TensorFlow

  • Programming experience with Python, DevOps, or comparable technologies

  • Working knowledge of fundamental AI/ML algorithms, object-oriented and functional design principles, and best-practice patterns

  • Experience with REST API development, NoSQL database design, and RDBMS design/optimization

What you need to know about the Singapore Tech Scene

The digital revolution has driven a constant demand for tech professionals across industries like software development, data analytics and cybersecurity. In Singapore, one of the largest cities in Southeast Asia, the demand for tech talent is so high that the government continues to invest millions into programs designed to develop a talent pipeline directly from universities while also scaling efforts in pre-employment training and mid-career upskilling to expand and elevate its workforce.

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