Your Responsibilities

• Develop and deploy machine learning models focused on anomaly detection to detect money laundering and fraudulent activity.
• Enhance and optimize data pipelines, integrating customer feedback to improve detection accuracy.
• Lead AI model governance and testing, ensuring models are interpretable, scalable, and reliable.
• Work closely with customers and stakeholders, translating feedback into model improvements and product enhancements.
• Build and deploy AI solutions, leveraging MLOps best practices for production-ready implementations.
• Collaborate with cross-functional teams (engineering, product, and business) to integrate AI solutions into Hawk AI’s offerings.
• Stay ahead of AI trends and financial crime strategies, developing expertise in financial crime detection methodologies.
• Mentor junior team members, providing technical guidance while remaining hands-on with development.

Your Profile

• 5+ years of experience in AI, machine learning, and data science, with hands-on deployment experience.
• Proficiency in Python and machine learning frameworks (PyTorch, TensorFlow, Keras).
• Strong experience with Kubernetes and Docker for containerized AI deployments.
• Cloud experience (AWS preferred, but not required), with knowledge of cloud-based AI model deployment.
• Expertise in SQL and standard data manipulation techniques.
• Anomaly detection experience—a plus if it's in relation to detecting financial crime patterns.
• MLOps experience, including model monitoring, retraining strategies, and production pipelines.
• Experience with AI testing platforms (e.g., MLflow) is a plus, as well as C++ experience.
• Full-stack mindset—ability to build, deploy, and refine AI solutions in production.
• Strong customer interaction skills—ability to understand customer needs and translate them into technical solutions.
• Structured thinker, capable of both technical innovation and hands-on implementation.
• Ph.D. or Master’s in Computer Science, Mathematics, Statistics, or a related field preferred but not required.

What We’re Looking For

• An end-to-end data scientist, comfortable with both model development and deployment.
• A strategic thinker who can identify patterns and devise effective countermeasures.
• A player-coach—hands-on and willing to guide others, but also able to lead technical initiatives.
• Someone curious and eager to learn about the world of financial crime.

This role is a unique opportunity to work at the intersection of AI and financial crime prevention, developing cutting-edge solutions that make a real-world impact.

Compensation Range: $180K - $215K