AI Engineer (PhD Required)

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    "description_html": "<div class=\"job_description\">\n\t\t\t\t\t<h1 dir=\"ltr\" style=\"margin-top:32px;margin-bottom:8px;\"><strong>AI Engineer</strong></h1><span style=\"font-size:14px;\"><strong>Employment Type: </strong>Full-Time<br><strong>Location</strong>: Remote, Singapore<br><strong>Level:</strong> Mid to Senior (PhD Required)</span><h2 dir=\"ltr\"><span style=\"font-size:18px;\"><strong>Transform AI Research into Real-World Impact</strong></span></h2><h2 dir=\"ltr\"><span style=\"font-size:16px;\"><strong>About the Role</strong></span></h2><span style=\"font-size:14px;\">As an AI Research Engineer at Pixalate, you'll bridge the gap between fundamental AI research and production systems that protect the digital ecosystem. Working with our Research team (AFAC) that has uncovered more than $100M in ad fraud and national security threats, you'll have the autonomy to pursue groundbreaking research while seeing your innovations deployed at scale within months, not years.<br><br>You'll lead research in emerging AI paradigms including autonomous agent systems, test-time compute optimization, and multimodal understanding - all applied to real-world challenges in digital safety and fraud detection.</span><h2 dir=\"ltr\"><span style=\"font-size:18px;\"><strong>Key Research Areas &amp; Responsibilities</strong></span></h2><h3 dir=\"ltr\"><span style=\"font-size:16px;\"><strong>Agentic AI Systems Development</strong></span></h3><ul><li dir=\"ltr\"><span style=\"font-size:14px;\">Design and implement multi-agent architectures for autonomous fraud detection and analysis</span></li><li dir=\"ltr\"><span style=\"font-size:14px;\">Develop sophisticated agent coordination systems using frameworks like LangChain, AutoGen, or custom architectures</span></li><li dir=\"ltr\"><span style=\"font-size:14px;\">Create tool-integrated AI agents capable of complex reasoning and decision-making</span></li><li dir=\"ltr\"><span style=\"font-size:14px;\">Research novel approaches to agent safety and alignment in production environments</span></li></ul><h3 dir=\"ltr\"><span style=\"font-size:16px;\"><strong>Advanced Reasoning &amp; Test-Time Compute</strong></span></h3><ul><li dir=\"ltr\"><span style=\"font-size:14px;\">Implement state-of-the-art reasoning systems inspired by recent breakthroughs (o1, DeepSeek-R1)</span></li><li dir=\"ltr\"><span style=\"font-size:14px;\">Optimize inference-time compute allocation for complex analytical tasks</span></li><li dir=\"ltr\"><span style=\"font-size:14px;\">Develop chain-of-thought and verification mechanisms for high-stakes decision making</span></li><li dir=\"ltr\"><span style=\"font-size:14px;\">Research novel approaches to scaling reasoning capabilities efficiently</span></li></ul><h3 dir=\"ltr\"><strong>Multimodal AI &amp; Knowledge Systems</strong></h3><ul><li dir=\"ltr\"><span style=\"font-size:14px;\">Build advanced multimodal models for analyzing video, image, text, and behavioral data</span></li><li dir=\"ltr\"><span style=\"font-size:14px;\">Develop sophisticated RAG (Retrieval-Augmented Generation) architectures:</span><ul><li dir=\"ltr\"><span style=\"font-size:14px;\">Design high-performance vector databases and hybrid search systems</span></li><li dir=\"ltr\"><span style=\"font-size:14px;\">Implement advanced chunking strategies and semantic understanding</span></li><li dir=\"ltr\"><span style=\"font-size:14px;\">Create context-aware retrieval mechanisms for complex documents</span></li></ul></li><li dir=\"ltr\"><span style=\"font-size:14px;\">Research cross-modal learning for fraud pattern detection</span></li></ul><h2 dir=\"ltr\"><strong>Required Qualifications</strong></h2><h3 dir=\"ltr\"><strong>Education &amp; Research Background</strong></h3><ul><li dir=\"ltr\"><span style=\"font-size:14px;\">PhD in Computer Science, AI, Machine Learning, or related field (or exceptional research track record)</span></li><li dir=\"ltr\"><span style=\"font-size:14px;\">Published research in peer-reviewed venues demonstrating expertise in:</span><ul><li dir=\"ltr\"><span style=\"font-size:14px;\">Large Language Models and transformer architectures</span></li><li dir=\"ltr\"><span style=\"font-size:14px;\">Agentic AI, autonomous systems, or multi-agent coordination</span></li><li dir=\"ltr\"><span style=\"font-size:14px;\">Multimodal learning or computer vision</span></li><li dir=\"ltr\"><span style=\"font-size:14px;\">Distributed systems and scalable ML</span></li></ul></li></ul><h3 dir=\"ltr\"><strong>Technical Expertise</strong></h3><ul><li dir=\"ltr\"><span style=\"font-size:14px;\">Expert proficiency in Python and deep learning frameworks (PyTorch preferred, TensorFlow)</span></li><li dir=\"ltr\"><span style=\"font-size:14px;\">Advanced experience with:</span><ul><li dir=\"ltr\"><span style=\"font-size:14px;\">Modern AI frameworks: LangChain, Hugging Face Transformers, Ray</span></li><li dir=\"ltr\"><span style=\"font-size:14px;\">Agent development and orchestration</span></li><li dir=\"ltr\"><span style=\"font-size:14px;\">RAG systems and vector databases</span></li><li dir=\"ltr\"><span style=\"font-size:14px;\">Distributed training frameworks and GPU optimization</span></li></ul></li><li dir=\"ltr\"><span style=\"font-size:14px;\">Strong understanding of:</span><ul><li dir=\"ltr\"><span style=\"font-size:14px;\">Transformer architectures and attention mechanisms</span></li><li dir=\"ltr\"><span style=\"font-size:14px;\">Reinforcement learning and reward modeling</span></li><li dir=\"ltr\"><span style=\"font-size:14px;\">Neural architecture search and AutoML</span></li><li dir=\"ltr\"><span style=\"font-size:14px;\">MLOps and production ML systems</span></li></ul></li></ul><h3 dir=\"ltr\"><strong>Research Skills</strong></h3><ul><li dir=\"ltr\"><span style=\"font-size:14px;\">Track record of novel algorithm development and innovation</span></li><li dir=\"ltr\"><span style=\"font-size:14px;\">Experience with large-scale experimentation and ablation studies</span></li><li dir=\"ltr\"><span style=\"font-size:14px;\">Proficiency in research tools: Weights &amp; Biases, MLflow, TensorBoard</span></li><li dir=\"ltr\"><span style=\"font-size:14px;\">Strong theoretical foundation in optimization, statistics, and linear algebra</span></li></ul><h2 dir=\"ltr\"><strong>Preferred Qualifications</strong></h2><ul><li dir=\"ltr\"><span style=\"font-size:14px;\">Experience with fraud detection, cybersecurity, or trust &amp; safety applications</span></li><li dir=\"ltr\"><span style=\"font-size:14px;\">Contributions to open-source AI projects</span></li><li dir=\"ltr\"><span style=\"font-size:14px;\">Industry research experience at leading AI labs (DeepMind, OpenAI, FAIR, etc.)</span></li><li dir=\"ltr\"><span style=\"font-size:14px;\">Experience translating research into production systems</span></li><li dir=\"ltr\"><span style=\"font-size:14px;\">Experience with:</span><ul><li dir=\"ltr\"><span style=\"font-size:14px;\">Mixture of Experts (MoE) architectures</span></li><li dir=\"ltr\"><span style=\"font-size:14px;\">Constitutional AI and alignment techniques</span></li><li dir=\"ltr\"><span style=\"font-size:14px;\">Efficient inference optimization (quantization, distillation)</span></li><li dir=\"ltr\"><span style=\"font-size:14px;\">Real-time streaming ML systems</span></li></ul></li></ul><h2 dir=\"ltr\"><strong>Benefits</strong><br><span style=\"font-size:14px;\">We focus on doing things differently and challenge each other to be the best we can be.</span></h2><ul><li dir=\"ltr\"><span style=\"font-size:14px;\">Monthly internet reimbursement</span></li><li dir=\"ltr\"><span style=\"font-size:14px;\">Casual, remote work environment</span></li><li dir=\"ltr\"><span style=\"font-size:14px;\">Hybrid, flexible hours</span></li><li dir=\"ltr\"><span style=\"font-size:14px;\">Opportunity for advancement</span></li><li dir=\"ltr\"><span style=\"font-size:14px;\">Fun annual team events</span></li><li dir=\"ltr\"><span style=\"font-size:14px;\">Being part of a high-performing team that wants to win and have fun doing it</span></li><li dir=\"ltr\"><span style=\"font-size:14px;\">Extremely competitive compensation</span></li></ul><span style=\"font-size:14px;\">We're particularly interested in candidates who can demonstrate both theoretical depth and practical implementation skills. Show us how your research can transform the landscape of online trust and safety.<br><br>Pixalate is an online trust and safety platform that protects businesses, consumers and children from deceptive, fraudulent and non-compliant mobile, CTV apps and websites. We're seeking a PhD-level AI Engineer to lead cutting-edge research in agentic AI systems, multimodal analysis, and advanced reasoning architectures that will directly impact millions of users worldwide.<br>Our software and data have been used to unearth multiple high profile criminal and illegal surveillance cases including:</span><ul><li dir=\"ltr\"><span style=\"font-size:14px;\">Gizmodo:<a href=\"https://gizmodo.com/apple-icloud-private-relay-ad-fraud-scam-research-1849803510\"> An iCloud Feature Is Enabling a $65 Million Scam, New Research Says</a></span></li><li dir=\"ltr\"><span style=\"font-size:14px;\">Adweek:<a href=\"https://www.adweek.com/programmatic/pixalate-ad-fraud-scheme-roku-murkiness-ctv/\"> A 7-Figure Ad Fraud Scheme Running on Roku Underlines Murkiness of CTV</a></span></li><li dir=\"ltr\"><span style=\"font-size:14px;\">Washington Post:<a href=\"https://www.washingtonpost.com/technology/2022/06/09/apps-kids-privacy/\"> Your kids&#8217; apps are spying on them</a></span></li><li dir=\"ltr\"><span style=\"font-size:14px;\">Pro Publica:<a href=\"https://www.propublica.org/article/google-display-ads-piracy-porn-fraud\"> Porn, Piracy, Fraud: What Lurks Inside Google&#8217;s Black Box Ad Empire</a></span></li><li dir=\"ltr\"><span style=\"font-size:14px;\">ABC7 News:<a href=\"https://www.youtube.com/watch?v=qhFAxvs-mBY\"> The State of Children's Privacy Online</a></span></li><li dir=\"ltr\"><span style=\"font-size:14px;\">NBC News:<a href=\"https://www.pixalate.com/blog/jalal-nasir-nbc-12news-apps-tracking-child\"> How many apps are tracking your children</a></span></li></ul><span style=\"font-size:14px;\">Our team of lawyers, data scientists, engineers, economists and researchers span globally with presence in California, New York, Washington DC, London and Singapore.</span><h1><span style=\"font-size:14px;\"><em>Pixalate is an equal opportunity employer committed to building a diverse team. We particularly encourage applications from underrepresented groups in AI research.</em></span></h1>",
    "description_text": "AI Engineer\n Employment Type: Full-Time\n Location : Remote, Singapore\n Level: Mid to Senior (PhD Required) Transform AI Research into Real-World Impact\n About the Role\n As an AI Research Engineer at Pixalate, you'll bridge the gap between fundamental AI research and production systems that protect the digital ecosystem. Working with our Research team (AFAC) that has uncovered more than $100M in ad fraud and national security threats, you'll have the autonomy to pursue groundbreaking research while seeing your innovations deployed at scale within months, not years.\nYou'll lead research in emerging AI paradigms including autonomous agent systems, test-time compute optimization, and multimodal understanding - all applied to real-world challenges in digital safety and fraud detection. Key Research Areas & Responsibilities\n Agentic AI Systems Development\n Design and implement multi-agent architectures for autonomous fraud detection and analysis\n Develop sophisticated agent coordination systems using frameworks like LangChain, AutoGen, or custom architectures\n Create tool-integrated AI agents capable of complex reasoning and decision-making\n Research novel approaches to agent safety and alignment in production environments\n Advanced Reasoning & Test-Time Compute\n Implement state-of-the-art reasoning systems inspired by recent breakthroughs (o1, DeepSeek-R1)\n Optimize inference-time compute allocation for complex analytical tasks\n Develop chain-of-thought and verification mechanisms for high-stakes decision making\n Research novel approaches to scaling reasoning capabilities efficiently\n Multimodal AI & Knowledge Systems\n Build advanced multimodal models for analyzing video, image, text, and behavioral data\n Develop sophisticated RAG (Retrieval-Augmented Generation) architectures: Design high-performance vector databases and hybrid search systems\n Implement advanced chunking strategies and semantic understanding\n Create context-aware retrieval mechanisms for complex documents\n Research cross-modal learning for fraud pattern detection\n Required Qualifications\n Education & Research Background\n PhD in Computer Science, AI, Machine Learning, or related field (or exceptional research track record)\n Published research in peer-reviewed venues demonstrating expertise in: Large Language Models and transformer architectures\n Agentic AI, autonomous systems, or multi-agent coordination\n Multimodal learning or computer vision\n Distributed systems and scalable ML\n Technical Expertise\n Expert proficiency in Python and deep learning frameworks (PyTorch preferred, TensorFlow)\n Advanced experience with: Modern AI frameworks: LangChain, Hugging Face Transformers, Ray\n Agent development and orchestration\n RAG systems and vector databases\n Distributed training frameworks and GPU optimization\n Strong understanding of: Transformer architectures and attention mechanisms\n Reinforcement learning and reward modeling\n Neural architecture search and AutoML\n MLOps and production ML systems\n Research Skills\n Track record of novel algorithm development and innovation\n Experience with large-scale experimentation and ablation studies\n Proficiency in research tools: Weights & Biases, MLflow, TensorBoard\n Strong theoretical foundation in optimization, statistics, and linear algebra\n Preferred Qualifications\n Experience with fraud detection, cybersecurity, or trust & safety applications\n Contributions to open-source AI projects\n Industry research experience at leading AI labs (DeepMind, OpenAI, FAIR, etc.)\n Experience translating research into production systems\n Experience with: Mixture of Experts (MoE) architectures\n Constitutional AI and alignment techniques\n Efficient inference optimization (quantization, distillation)\n Real-time streaming ML systems\n Benefits\n We focus on doing things differently and challenge each other to be the best we can be.\n Monthly internet reimbursement\n Casual, remote work environment\n Hybrid, flexible hours\n Opportunity for advancement\n Fun annual team events\n Being part of a high-performing team that wants to win and have fun doing it\n Extremely competitive compensation\n We're particularly interested in candidates who can demonstrate both theoretical depth and practical implementation skills. Show us how your research can transform the landscape of online trust and safety.\nPixalate is an online trust and safety platform that protects businesses, consumers and children from deceptive, fraudulent and non-compliant mobile, CTV apps and websites. We're seeking a PhD-level AI Engineer to lead cutting-edge research in agentic AI systems, multimodal analysis, and advanced reasoning architectures that will directly impact millions of users worldwide.\nOur software and data have been used to unearth multiple high profile criminal and illegal surveillance cases including: Gizmodo: An iCloud Feature Is Enabling a $65 Million Scam, New Research Says\n Adweek: A 7-Figure Ad Fraud Scheme Running on Roku Underlines Murkiness of CTV\n Washington Post: Your kids’ apps are spying on them\n Pro Publica: Porn, Piracy, Fraud: What Lurks Inside Google’s Black Box Ad Empire\n ABC7 News: The State of Children's Privacy Online\n NBC News: How many apps are tracking your children\n Our team of lawyers, data scientists, engineers, economists and researchers span globally with presence in California, New York, Washington DC, London and Singapore. Pixalate is an equal opportunity employer committed to building a diverse team. We particularly encourage applications from underrepresented groups in AI research.",
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