Applied AI Scientist (PhD Required)

Applied AI Scientist Employment Type: Full-Time Location : Remote, Singapore Level: Mid to Senior (PhD Required) About the Role We're looking for a quantitatively-strong data professional who can bridge rigorous statistical thinking with hands-on AI development. You'll work across Pixalate's full product suite — trust & safety, ad fraud detection, brand safety, and more — using your background in statistics and ML to build intelligent agents and automated pipelines that keep our data accurate, our models honest, and our products reliable. This role is for someone who understands data deeply and can translate that into working AI systems that do the checking, flagging, and quality assurance at scale. Responsibilities Analyze traffic, behavioral, and signals data to identify patterns, anomalies, and data quality issues Translate complex quantitative findings into clear, actionable recommendations for engineering, product, and cross-functional teams Design and maintain AI agents, dashboards and reporting pipelines to track data quality, trends, and product health over time Partner with engineering and product teams to ensure data quality and integrity across product pipelines Collaborate with AI/ML teams to close the feedback loop between QA findings and model improvements Support data needs across Pixalate's product portfolio — including supply-side intelligence, MFA detection, seller/app ratings, and compliance-related products What We're Looking For Must-Have PhD in Statistics, Mathematics, Data Science, Computer Science, or a related quantitative field 3–6 years of experience in a data science, ML, or data analytics role Strong statistical foundation — you understand distributions, hypothesis testing, model evaluation, and where things go wrong Hands-on experience building with LLMs and AI agents, including prompt engineering, tool use, and designing agentic workflows using existing frameworks (e.g. LangChain, LlamaIndex, CrewAI, AutoGen, or similar) Proficiency in Python and SQL Ability to think critically about data quality and model outputs — you're naturally skeptical and rigorous Clear written and verbal communication skills Nice-to-Have Prior experience in cybersecurity, fraud detection, trust & safety, or digital advertising ecosystems Exposure to multi-agent orchestration patterns Comfort working in fast-moving environments with evolving product requirements Benefits We focus on doing things differently and challenge each other to be the best we can be. Monthly internet reimbursement Casual, remote work environment Hybrid, flexible hours Opportunity for advancement Fun annual team events Being part of a high-performing team that wants to win and have fun doing it Extremely competitive compensation 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. 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. Our 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 Adweek: A 7-Figure Ad Fraud Scheme Running on Roku Underlines Murkiness of CTV Washington Post: Your kids’ apps are spying on them Pro Publica: Porn, Piracy, Fraud: What Lurks Inside Google’s Black Box Ad Empire ABC7 News: The State of Children's Privacy Online NBC News: How many apps are tracking your children 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.