Senior AI / Machine Learning Engineer — Fraud Detection
📍 Location: San Jose, California, United States (Hybrid)
🏢 Industry: Software Development
💼 Work Setting: Hybrid
Are you passionate about leveraging Artificial Intelligence and Machine Learning to combat fraud, abuse, and emerging digital threats? We are seeking a highly experienced Senior AI/ML Engineer to design, build, and scale intelligent risk detection solutions. This is a hands-on opportunity to work across machine learning, data engineering, and backend systems while driving innovation in fraud prevention, anomaly detection, identity protection, and automated decision-making.
What You'll Do
- Design, develop, and deploy advanced machine learning models for fraud detection, risk assessment, anomaly detection, and abuse prevention.
- Create and optimize risk signals using large-scale behavioral, device, network, account, session, and transaction data.
- Integrate AI and ML capabilities into real-time risk evaluation and automated response systems.
- Utilize modern AI technologies, including Large Language Models (LLMs) and intelligent agents, to enhance threat detection, investigation, and classification workflows.
- Research emerging attack trends and translate findings into actionable detection strategies, models, and preventive controls.
- Measure and improve system performance across accuracy, scalability, latency, operational efficiency, and customer experience.
- Monitor model health, evaluate performance, and address model drift as threat landscapes evolve.
- Collaborate with cross-functional teams to deliver robust, production-ready AI solutions.
What You'll Need to Succeed
- 8+ years of experience developing and operating production-grade machine learning systems, preferably in risk management, fraud prevention, trust & safety, cybersecurity, or similar domains.
- Strong expertise in Machine Learning, Python, SQL, and modern ML frameworks such as PyTorch.
- Proven experience across the complete ML lifecycle, including feature engineering, model development, deployment, monitoring, and optimization.
- Solid software engineering and data engineering skills with experience building scalable data and backend systems.
- Hands-on experience with LLMs, AI agents, or generative AI applications in detection and automation scenarios.
- Strong analytical thinking, technical leadership, and the ability to solve complex and evolving challenges.
- Bachelor's degree in Computer Science, Statistics, Mathematics, Engineering, or a related field. Advanced qualifications are advantageous.
Preferred Qualifications
- Experience with identity verification, device intelligence, behavioral analytics, network intelligence, or proxy/VPN detection techniques.
- Knowledge of real-time risk scoring and automated control frameworks.
- Experience with AI-assisted investigation platforms and human-in-the-loop evaluation systems.
- Familiarity with distributed systems, large-scale data processing, and high-throughput data pipelines.
- A proactive mindset for identifying and anticipating evolving attack strategies and adapting defenses accordingly.
Work Model
- Hybrid work environment with a minimum of three days per week in the office.