What are the responsibilities and job description for the Director of Data Science & AI position at Robert Half?
Responsibilities:
• Design and implement machine learning systems to detect anomalies, identify malicious activities, and adapt to evolving threat vectors within decentralized network environments.
• Develop real-time intelligence pipelines that process large-scale data signals into actionable insights with speed and accuracy.
• Lead the end-to-end lifecycle of AI model development, including designing, training, testing, and deploying models tailored for security and anomaly detection.
• Collaborate with infrastructure and platform teams to optimize data telemetry, build labeled datasets, and scale data quality across the organization.
• Partner with cross-functional teams, including Security, Platform, and Network Engineering, to integrate AI solutions seamlessly into system architecture.
• Recruit, mentor, and manage a team of elite machine learning engineers and research scientists, fostering innovation and excellence in a dynamic environment.
• Stay ahead of emerging threats by analyzing attack patterns, adversarial behaviors, and cutting-edge detection methods to refine defenses.
• Architect scalable AI and inference systems that balance performance, privacy, and security while adapting to evolving demands.
• Translate research innovations into production-grade systems that enhance threat detection and response capabilities.
• At least 10 years of experience in machine learning, with a proven ability to apply AI models to real-world challenges such as security or large-scale data environments.
• Deep understanding of threat modeling, including common attack vectors, evasive behaviors, and adversarial tactics in network and identity systems.
• Expertise in designing and deploying machine learning models that operate robustly in production environments.
• Strong architectural skills, with the ability to design scalable and adaptive inference systems that prioritize security and performance.
• Leadership experience in building and scaling AI or data teams within high-growth, ambiguous environments.
• Proficiency in Python and modern machine learning frameworks such as PyTorch and TensorFlow.
• Familiarity with cloud technologies, data visualization, and tools like Apache Kafka, Hadoop, Spark, and AWS.
• Demonstrated technical rigor and curiosity, staying updated on advances in detection algorithms, graph modeling, and sequential analysis.
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Salary : $140,000 - $200,000