Junior AI Project Manager / Associate Tech PM

• Bachelor's degree in Computer Science, Data Science, Engineering, Business, or a related field. Fresh graduates are also welcome to apply.

• Previous internship experience in project management, tech operations, data analysis, or product management is a strong plus.

• Proven track record of successfully delivering data science, machine learning, or AI projects to production.

• Strong conceptual understanding of Artificial Intelligence, Machine Learning, Natural Language Processing and Generative AI.

• Understanding of data pipelines, data architecture, and the importance of data quality in model training.

• Excellent analytical and problem-solving skills, with the ability to manage the inherent uncertainties and experimental nature of AI projects.

A Vibrant and Diverse Workplace: Immerse yourself in a dynamic, multi-cultural environment with colleagues from over 15 nationalities (and growing!). We celebrate diversity and foster a global perspective.

Incentives in the Web3 Space: Be a part of the future and align your success with the growth of our innovative projects.

Direct Impact and Flat Structure: Your voice matters. We operate with a flat organizational structure, ensuring your ideas are heard and implemented quickly.

Comfortable and Creative Atmosphere: Embrace a relaxed and productive work environment with casual attire.

Opportunities Across the Ecosystem: Expand your horizons by collaborating with various subsidiary brands within the Animoca Brands network, gaining exposure to a wide range of projects and technologies.

Comprehensive Benefits Package: We care about your well-being. Enjoy a comprehensive benefits package, including medical, life, and transportation allowances.

Personal Information Collection Statement:

Personal data provided by the Job Applicant will be used strictly in accordance with the Employer's Personal Data Policies, a copy of which will be provided immediately upon his/her request. All classified data will be treated confidentially within the Human Resources & Administration Department. Personal data of unsuccessful applicants may be retained for a period of up to 3 months.

Animoca Brands Corporation Limited (ACN: 122 921 813) is a Web3 leader that leverages tokenization and blockchain to deliver digital property rights to consumers, helping to establish the open metaverse and its associated network effects. Animoca Brands realizes its mission via three integrated business pillars: operating Web3 businesses to advance blockchain adoption with native projects such as Moca Network, Anichess, The Sandbox, Open Campus, NEOM Web3 initiatives, and a regulated stablecoin project in partnership with Standard Chartered and HKT; providing digital asset advisory services including tokenomics advisory, liquidity provisioning, and institutional research to help external Web3 projects grow; and investment management, with a portfolio of investments in over 540 companies including industry leaders Pudgy Penguins, Yuga Labs, Axie Infinity, Polygon, Consensys, Magic Eden, OpenSea, Dapper Labs, YGG, and many others.

We are seeking an AI Project Manager to lead the planning, execution, and delivery of innovative Artificial Intelligence and Machine Learning initiatives. In this role, you will act as the critical bridge between our business stakeholders, data scientists, and engineering teams. You will be responsible for navigating the unique complexities of AI projects-from data collection and model training to deployment and performance monitoring - ensuring solutions are delivered on time, within scope, and drive real business value

• Lead the full lifecycle of AI project, including requirement gathering, feasibility assessment, data strategy, model development, testing, and production deployment.

• Serve as the primary liaison between business teams and technical teams, translating complex business requirements into clear technical specifications and user stories.

• Oversee specific AI phases such as data labeling, model training iterations, validation, and managing expectations around model accuracy and performance.

• Identify potential project risks early and implement mitigation strategies.

• Provide regular updates to leadership, clearly communicating technical bottlenecks, model metrics, and project progress in business-friendly terms.