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About Finoverse Finoverse is the largest global tech network, specialising in bringing people and experiences together that lead to transformative change. Since 2015, Finoverse has spearheaded world-class experiential FinTech and Web3 events, celebrated the voices of the next generation, and created a collaborative space valued by over 202,000 senior executives, founders, investors, and family offices from more than 130 countries, across Asia, the Middle East, and North America. In 2025 the company launched Finoverse AI, the team behind Samantha, the AI community host that conducts assessments and in-depth interviews on WhatsApp at scale. Finoverse has offices in Hong Kong and Shenzhen. With offices in Hong Kong, Shenzhen and Dubai, Finoverse sparks conversations and connects professionals - from regulators to entrepreneurs, from big banks to start-ups, from technology to traditional finance. Why Join Us Finoverse sits at a unique crossroads where generational wealth holders seek innovation and where builders seek strategic capital. Our team operates in an energetic, globally minded culture with daily exposure to top business leaders, family office principals, regulators, and pioneering founders. We want people who thrive at this intersection, bringing bold ideas, entrepreneurial energy, and a passion for shaping the future of finance and wealth. Making a Positive Impact is in Our DNA We innovate in what we do and who we are as individuals. Finoverse empowers and unites those who share the same core values as us to make positive contributions and instil transformative changes in our network and community. Your role at Finoverse AI Development & Maintenance Design, develop, and maintain AI applications, with a focus on integrating and fine-tuning LLMs for specific use cases. Implement and optimize AI pipelines, including data preprocessing, model training, inference, and deployment. Evaluate and compare the performance of different LLMs for tasks such as natural language understanding, summarization, and automation. Stay updated with the latest advancements in AI/ML and propose innovative solutions to enhance our products. Testing & Evaluation Develop and execute test plans to validate the accuracy, efficiency, and reliability of AI models and applications. Benchmark and compare LLMs against predefined metrics (e.g., accuracy, latency, cost, and scalability). Identify biases, limitations, and edge cases in AI models, and implement mitigation strategies. Document test results, model performance, and recommendations for improvement. Software Engineering Write clean, maintainable, and efficient code following best practices. Collaborate with team members to design and implement scalable software architectures. Debug, profile, and optimize code to improve performance and resource utilization. Participate in code reviews, providing constructive feedback and incorporating feedback from peers. Develop and maintain CI/CD pipelines to automate testing, build, and deployment processes. Troubleshoot and resolve technical issues in production and development environments. Contribute to technical documentation, including API specs, architecture diagrams, and user guides. Collaboration & Communication Work closely with product managers and other engineers to align AI solutions with business goals. Communicate complex technical concepts clearly and effectively to both technical and non-technical stakeholders. Present findings, progress, and recommendations in team meetings, demos, and reports. Who you are Bachelor’s degree in Computer Science, Software Engineering, AI/ML, or a related field (or equivalent practical experience). 2-4 years of professional experience in software engineering, with at least 1 year focused on AI/ML or LLM development. Portfolio or examples of past AI/software projects (e.g., GitHub repositories, blog posts, or published papers) are a plus. Rich knowledge of Chinese culture and its applications; candidates from Chinese Mainland, based in Hong Kong or Shenzhen, are strongly preferred. Abilities we are looking for Technical Skills Programming Languages: Proficiency in Typescript and Python, and experience with other languages. AI/ML Frameworks: Hands-on experience with libraries such as: Hugging Face Transformers, LangChain, or LlamaIndex PyTorch, TensorFlow, or JAX Scikit-learn, Pandas, or NumPy LLM Experience: Familiarity with working with LLMs (e.g., fine-tuning, prompt engineering, RAG, or model evaluation). Software Engineering: Experience with version control (e.g., Git) and collaborative development workflows. Knowledge of cloud platforms (AWS preferred; GCP or Azure optional) and containerization (Docker, Kubernetes). Understanding of RESTful APIs, microservices, and scalable system design. Testing & Debugging: Experience with unit testing, integration testing, and debugging tools. Soft Skills Communication: Excellent written and spoken English skills, with the ability to articulate technical ideas clearly and collaborate effectively in a team. Problem-Solving: Strong analytical and critical thinking skills to diagnose and resolve complex technical challenges. Adaptability: Ability to learn quickly and adapt to new technologies, tools, and methodologies. Experience with MLOps tools (e.g., MLflow, Weights & Biases, or Kubeflow). Knowledge of vector databases. Contributions to open-source AI/ML projects. Familiarity with ethical AI practices, including bias mitigation and responsible AI deployment.
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.