AI Scientist

Hytech is a leading management consulting firm headquartered in Australia and Singapore, specialising in digital transformation for fintech and financial services companies. We provide comprehensive consulting solutions, as well as middle- and back-office support, to empower our clients with streamlined operations and cutting-edge strategies. With a global team of over 2,000 professionals, Hytech has established a strong presence worldwide, with offices in Australia, Singapore, Malaysia, Taiwan, Philippines, Thailand, Morocco, Cyprus, Dubai and more. Why Join Us?At Hytech, we are redefining how millions of users discover and engage with digital content. We believe that the future of content is intelligent, personalized, and growth-driven — powered by cutting-edge machine learning and large-scale AI systems. As part of the Content & Growth AI Team , you’ll play a central role in shaping content discovery, driving user engagement, and unlocking the next wave of platform growth. From personalized feeds and real-time hot topic detection to AI-generated content (AIGC) strategies, we combine algorithmic excellence with product intuition to amplify impact. You’ll join a world-class team of engineers and researchers focused on building scalable, high-performance AI systems that power content recommendations, trending detection, and multimodal user engagement. What You’ll Do Design and optimize large-scale recommendation algorithms to enhance personalized user experiences across feeds, content hubs, and interactive touchpoints. Build intelligent content growth pipelines, including real-time hot topic detection, viral content diffusion modeling, and trending topic amplification. Develop and integrate AIGC-aware recommendation systems, enabling dynamic ranking and generation strategies based on user preferences and market signals. Apply state-of-the-art retrieval, ranking, and re-ranking models to refine recommendation precision, diversity, and freshness. Leverage sequence models (Transformers, RNNs)and graph-based methods to model user behavior over time and across content types. Employ multi-modal learning (text, image, video, social graphs)to improve understanding of content and boost personalization effectiveness. Collaborate cross-functionally with product, data, and infrastructure teams to define and drive content growth strategies aligned with business objectives. Run large-scale A/B tests , perform causal inference and behavioral analytics to quantify impact, guide iteration, and scale success. Contribute to system architecture, model deployment pipelines, and performance optimization for real-time inference at scale. Stay at the frontier of recommendation, generative AI, and content intelligence research , translating innovation into production impact. Qualifications 5+ years of experience in recommendation systems, content AI, or growth-focused machine learning . Proven track record in developing large-scale personalized recommendation engines using deep learning, collaborative filtering, or hybrid models. Hands-on experience with hot topic mining , entity co-occurrence graph modeling , or event-based content surfacing is a strong plus. Solid understanding of retrieval-ranking architectures , cold-start mitigation, and user lifecycle-based personalization. Experience with deep learning frameworks (e.g., TensorFlow, PyTorch), vector search (e.g., FAISS, Milvus), and knowledge-enhanced models. Proficiency in big data processing (Spark, Hive, Hadoop) and distributed computing frameworks. Strong problem-solving and communication skills; ability to drive cross-functional collaborations. Passion for content ecosystems, user growth loops, and delivering measurable impact through intelligent systems. Preferred Qualifications Background in AIGC integration , content generation ranking, or LLM-based user interaction modeling. Experience working in high-growth environments , social media, or consumer-facing recommendation platforms. Familiarity with user engagement funnels , content virality metrics, and experimentation platforms (e.g., Optimizely, internal A/B infra). Research exposure in causal inference, reinforcement learning , or multimodal retrieval . What We Offer Competitive compensation and performance-based incentives. Opportunity to lead cutting-edge initiatives at the intersection of AI and content growth. Access to world-class infrastructure and the freedom to ship impactful systems. A collaborative, fast-paced culture that values curiosity, speed, and innovation. Details Seniority level: Mid-Senior level Employment type: Full-time Job function: Information Technology, Engineering, and Strategy/Planning Industries: IT System Custom Software Development and Securities and Commodity Exchanges #J-18808-Ljbffr