Engineering | Remote, India | Full-Time
Search Platform's mission is to power world-class, trusted cross-product knowledge search and discovery for people and agents across all of Atlassian's product and agentic surfaces. We are looking for a product-minded ML systems leader with deep expertise in applied machine learning and production ML infrastructure.
As a
Senior Machine Learning Systems Engineer, you'll be at the intersection of search, machine learning and experimentation. You will work directly with cross-functional teams to deliver innovative, ML-powered solutions that directly impact millions of customers.
- Collaborate with your teammates to solve complex problems, from technical design to launch.
- Partner across engineering teams to take on company-wide initiatives spanning multiple projects.
- Build proof-of-concept (POC) systems and evolve them into reliable, scalable services.
- Contribute to best practices in model deployment, monitoring, and evaluation.
- Work closely with other ML engineers, backend developers, and product teams to ship end-to-end innovations.
- Develop robust feature engineering practices to ingest, process, and serve features for offline training and online inference at scale.
- Develop and deploy ranking models to optimize ranking to improve the user experience and achieve business objectives
- Develop tools and infra to support rapid experimentation, evaluation, and deployment of prototypes
- Optimize latency, throughput, and resource efficiency for search workloads.
- Transfer your depth of knowledge from your current language to excel as a Software Engineer
- Communicate complex technical concepts clearly to both technical and non-technical stakeholders, creating concise artifacts for peers, partners, and leadership.
- Deliver code reviews, documentation & bug fixes within a strong engineering culture
- Mentor junior members of the team.
- 8+ years experience in multiple hands-on software/technology leadership roles, with end-to-end responsibility through the software development lifecycle
- Proven experience developing, deploying, and maintaining end-to-end ML systems, from data engineering to model serving and monitoring.
- Extensive experience designing and building scalable, fault-tolerant, and high-performance distributed systems for machine learning.
- Deep experience implementing MLOps, CI/CD pipelines, and automation for continuous training, deployment, and monitoring of ML models.
- Expertise with one or more prominent languages such as Java, Python, Kotlin, Go, or TypeScript is required.
- Understanding of SaaS, PaaS, IaaS industry with hands-on experience with public cloud offerings (e.g., AWS, GCP, or Azure)
- Knowledge to evaluate trade-offs between correctness, robustness, performance, space and time
- Consider the customer impact when making technical decisions
Benefits & PerksAtlassian offers a wide range of perks and benefits designed to support you, your family and to help you engage with your local community. Our offerings include health and wellbeing resources, paid volunteer days, and so much more. To learn more, visit
