Principal Machine Learning Systems Engineer, Search Platform

Atlassian
Bengaluru, India
Workplace: RemoteFull timeFunction: IT Operations (Systems/Network Admin)Experience: 10+ yearsSkills: ["Product judgment","Technical innovation","Leadership","Mentoring","Communication"]

Own the end-to-end lifecycle of production ML for Atlassian’s cross-product Search Platform, from framing and experimentation to architecture, launch, and continuous improvement. Lead initiatives that improve document understanding, enrichment, embeddings, and semantic indexing, partnering with Search Quality and product teams on online outcomes. Build scalable distributed ML/data systems across heterogeneous sources, balancing quality, freshness, correctness, reliability, latency, and cost.

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FursaFursa
Atlassian
Atlassian
1 day ago

Principal Machine Learning Systems Engineer, Search Platform

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Last checked: 10 hours agoStatus: Live

Job Summary

Own the end-to-end lifecycle of production ML for Atlassian’s cross-product Search Platform, from framing and experimentation to architecture, launch, and continuous improvement. Lead initiatives that improve document understanding, enrichment, embeddings, and semantic indexing, partnering with Search Quality and product teams on online outcomes. Build scalable distributed ML/data systems across heterogeneous sources, balancing quality, freshness, correctness, reliability, latency, and cost.
Location: Bengaluru, India
Workplace: Remote
Employment Type: Full time
Job Function: IT Operations (Systems/Network Admin)
Seniority: Sr. Manager level

Key Responsibilities

  • •Set technical direction for a major ML-powered search data and indexing capability, translating customer and product problems into measurable ML and systems outcomes.
  • •Advance and productionize ML approaches for document understanding, enrichment, embeddings/semantic representations, and index construction/evolution.
  • •Own the ML lifecycle end to end (data/feature strategy through deployment, offline evaluation, monitoring, and continuous improvement), partnering on online outcome measurement.
  • •Design scalable ML and distributed-data systems across heterogeneous sources while balancing retrieval quality, freshness, correctness, reliability, latency, and cost.
  • •Lead difficult technical decisions across partner teams and advance group engineering craft through hands-on work, mentoring, and clear communication.

Pay and Benefits

Equity and Bonus:Equity

Key Requirements

  • •10+ years building models or production ML systems, with deep applied ML in search, information retrieval, recommendation, NLP, LLMs, or content understanding.
  • •Experience designing, building, and operating production ML systems across data prep, features/representations, model development, deployment, evaluation, and observability/drift.
  • •Strong software, distributed-systems, and data-engineering depth including large-scale processing, indexing, failure recovery, schema evolution, scalability, and cost.
  • •Track record evaluating new research/industry techniques and turning results into reliable production capabilities.
  • •Product judgment to define measurable outcomes and choose among rules, classical ML, deep learning, and LLM-based approaches.
Experience:10+ years
Skills:Product judgmentTechnical innovationLeadershipMentoringCommunication
Tech Stack:Machine LearningSearchInformation retrievalRecommendationNLPLLMsEmbeddingsSemantic representationsIndexingDistributed systems

Company Brief

Atlassian
Atlassian develops collaboration and workflow software—Jira, Confluence, Trello, Loom and more—used by teams for project management, software development, and IT service management across enterprises worldwide.
Industry: Developer Tools
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: Sydney, Australia
Founded: 2002
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