Atlassian's Trust Engineering team is looking to build and scale AI/ML platforms and solutions to enhance security, privacy, anti-abuse, and compliance, aiming to build customer trust through advanced systems.
Requirements
Deep expertise in Python, Go, or Java, with the ability to write performant, production-quality code; familiarity with SQL, Spark, and cloud data environments (e.g., AWS, GCP, Databricks).
Experience building and scaling ML models for business-critical applications, ideally in security, privacy, anti-abuse, or compliance domains.
Demonstrated ability to solve ambiguous, complex problems and drive projects from ideation to production.
Experience in AI safety, responsible AI, or regulatory compliance for ML systems.
Background in privacy engineering, anti-abuse, security automation, or GRC platforms.
Experience developing deep learning models, LLMs, or privacy-preserving ML techniques.
Experience mentoring and growing high-performing ML teams.
Responsibilities
Lead AI/ML Strategy for Trust: Drive the development and implementation of advanced machine learning algorithms and AI systems for Trust, Security, Product Abuse, and Compliance use cases (e.g., threat detection, vulnerability management, privacy automation, AI safety).
Architect and Scale ML Platforms: Design and build scalable, secure, and reliable ML infrastructure and pipelines, ensuring compliance with privacy and regulatory requirements.
AI Safety and Responsible AI: Develop and champion AI safety practices, including output moderation, explainability, and alignment with evolving regulatory frameworks.
Cross-Functional Collaboration: Partner with product, engineering, security, privacy, and analytics teams to deliver transformative AI/ML solutions that enhance Atlassian’s trust posture.
Mentorship and Leadership: Mentor and guide ML engineers and data scientists, fostering a culture of technical excellence, innovation, and continuous improvement.
Innovation and Research: Stay at the forefront of AI/ML research, evaluating and applying the latest techniques (e.g., LLMs, anomaly detection, privacy-preserving ML) to real-world Trust challenges.
Platform Enablement: Build reusable ML services and APIs that empower other teams to integrate AI/ML into their products and workflows.
Other
Bachelor’s, Master’s, or PhD in Computer Science, Statistics, Mathematics, or a related field, or equivalent practical experience.
12+ years of industry experience in machine learning, data science, or AI, with a proven track record of delivering production-grade ML systems.
Strong communication skills, able to explain complex ML concepts to diverse audiences and influence stakeholders.
Agile development mindset, with a focus on iterative improvement and business impact.
Atlassians can choose where they work – whether in an office, from home, or a combination of the two.
