Engineering Manager, Machine Learning
RunwayFull Time
Junior (1 to 2 years), Senior (5 to 8 years)
Candidates should have 5+ years of experience developing modern tech stacks and 2+ years managing a development team, specifically in an AI/ML context. Strong proficiency with AWS or Azure, Python, and ideally Node.js is required, along with solid hands-on experience in the entire ML lifecycle, including data pipelines, model training, deployment, monitoring, and MLOps. Bonus experience includes working with large-scale data processing and big data technologies, familiarity with deep learning frameworks, experience with NLP or computer vision, and an understanding of ethical AI principles.
The Engineering Manager, AI/ML will lead the technical direction and execution for AuditBoard’s AI/ML initiatives. They will mentor, inspire, and grow a diverse team of engineers, managing and developing the team through hiring, retention, and capability building. Responsibilities include developing strong relationships with cross-functional partners, owning the end-to-end build and delivery of AI/ML models, services, and features, and continuously improving the product lifecycle. The manager will also work cross-functionally to integrate AI/ML capabilities and collaborate with Product Management to define goals and roadmaps, while iterating on agile best practices.
GRC software for audit and compliance
AuditBoard provides Governance, Risk, and Compliance (GRC) software solutions for large enterprises, including many Fortune 500 companies. Its platform automates and manages audit, risk, and compliance programs in real time, enabling teams to collaborate and report from anywhere. The company operates on a Software-as-a-Service (SaaS) model, offering specialized modules for different GRC aspects, which simplifies complex tasks and improves efficiency. AuditBoard's goal is to empower organizations to effectively manage their compliance and risk management needs.