Senior Principal Machine Learning Engineer, Search Platform

Atlassian
Seattle, San Francisco, Mountain View, New York, Austin
Workplace: RemoteFull timeFunction: Data Science & Machine LearningExperience: 12+ yearsSkills: ["Technical leadership","Communication","Experimentation","Rigorous evaluation","Influencing architecture"]

Design and lead ML architecture for Atlassian’s cross-product search, focusing on ranking, retrieval, inference pipelines, and serving infrastructure. Drive measurable improvements in search quality, latency, cost, and reliability through experimentation and evaluation frameworks. Identify high-leverage research directions and take them from prototype to production, setting standards for rollout safety and observability while mentoring engineers across search serving.

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FursaFursa
Atlassian
Atlassian
3 days ago

Senior Principal Machine Learning Engineer, Search Platform

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Source: Company careers pageValidated by: Fursa AI
Last checked: 6 hours agoStatus: Live

Job Summary

Design and lead ML architecture for Atlassian’s cross-product search, focusing on ranking, retrieval, inference pipelines, and serving infrastructure. Drive measurable improvements in search quality, latency, cost, and reliability through experimentation and evaluation frameworks. Identify high-leverage research directions and take them from prototype to production, setting standards for rollout safety and observability while mentoring engineers across search serving.
Location: Seattle, San Francisco, Mountain View, New York, Austin
Workplace: Remote
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Set the technical direction for ML-based search serving, including ranking models, retrieval architectures, inference pipelines, and serving infrastructure.
  • •Drive measurable improvements in search quality, latency, serving cost, and system reliability using rigorous experimentation and engineering practices.
  • •Lead model optimization end-to-end, including quantisation, distillation, batching strategies, hardware-aware inference, and latency/accuracy trade-offs.
  • •Define and enforce ML systems standards for evaluation, shadow traffic testing, rollout safety, and production observability.
  • •Mentor and elevate senior engineers across Search Serving and partner with Search Quality, ML Platform, and product teams to align roadmaps.

Pay and Benefits

Perks:Health InsuranceDentalVisionPaid LeavePaid Volunteer

Key Requirements

  • •12+ years of engineering experience with significant depth in ML systems and production ML infrastructure.
  • •Design and ship low-latency ML serving systems at scale, including sub-100ms ranking, retrieval, or inference pipelines.
  • •Deep expertise in information retrieval and search, including dense/sparse retrieval, neural reranking, hybrid search, and learning-to-rank.
  • •End-to-end model optimization for large-scale serving, including Triton, TorchServe, vLLM (or equivalent) and GPU/CPU optimization with autoscaling.
  • •Demonstrated technical leadership without authority, influencing architecture and decisions across team and org boundaries.
Experience:12+ yearsMachine learningSearchRetrievalProduction MLOnline experimentation
Skills:Technical leadershipCommunicationExperimentationRigorous evaluationInfluencing architecture
Tech Stack:TritonTorchServeVLLMGPUCPUGCPAWSQuantisationDistillationAutoscaling

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
Glassdoor
Glassdoor: 3.1
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