Base Salary
$226k - $356k/yr
Responsibilities
- Set technical direction for ML-based search serving, including ranking models, retrieval architectures, inference pipelines, and serving infrastructure.
- Improve search quality, latency, serving cost, and system reliability through experimentation and engineering.
- Lead model optimization involving quantization, distillation, batching, hardware-aware inference, and latency/accuracy trade-offs.
- Define standards for model evaluation, shadow traffic testing, rollout safety, and production observability.
- Mentor senior engineers and raise the technical bar through design reviews, architecture decisions, and hands-on guidance.
- Partner with Search Quality, ML Platform, and product teams to align roadmaps and unblock high-impact work.
- Identify high-leverage search research directions and drive them from prototype to production.
Requirements
- 12+ years of engineering experience with significant depth in ML systems and production ML infrastructure.
- Proven experience designing and shipping low-latency ML serving systems at scale, including sub-100ms ranking, retrieval, or inference pipelines.
- Deep expertise in information retrieval and search, including dense and sparse retrieval, neural reranking, hybrid search, and learning-to-rank.
- Strong knowledge of model optimization and large-scale serving infrastructure, including model serving frameworks, GPU/CPU optimization, and autoscaling.
- Experience influencing architecture and technical decisions across team and organizational boundaries without direct authority.
- Experience identifying high-leverage research directions and delivering them from prototype to production.
- Experience with online experimentation and rigorous ML systems evaluation frameworks.
- Strong communication skills for explaining complex technical trade-offs to technical and non-technical audiences.
- Preferred experience with enterprise search, multi-tenant serving, compliance-constrained environments such as FedRAMP or isolated cloud, or cloud-native ML on GCP or AWS.
Benefits
- Flexible work arrangement allowing employees to work from an office, home, or a combination of the two, with hiring available in countries where Atlassian has a legal entity.
- Health and wellbeing resources, paid volunteer days, and additional benefits and perks.
- The role may be eligible for benefits, bonuses, commissions, and equity.
Tech Stack
Categories
About Atlassian
Atlassian powers the collaboration that helps teams accomplish what would otherwise be impossible alone. From space missions and motor racing to bugs in code and IT requests, no task is too large or too small with the right team, the right tools, and the right practices. Over 300,000 global companies and 80% of the Fortune 500 rely on Atlassian’s software, like Jira, Confluence, Loom, and Trello, to help their teams work better together and deliver quality results on time. With our 300,000+ customers and team of 10,000+ Atlassians, we are building the next generation of team collaboration and productivity software. We believe the power of teams has the potential to change the world — one that is more open, authentic, and inclusive.