Senior Principal Machine Learning Systems Engineer, Search Platform

Atlassian
Seattle, San Francisco, Mountain View, New York, Austin
Workplace: RemoteFull timeFunction: IT Operations (Systems/Network Admin)Skills: ["Communication","Technical leadership","Cross-team collaboration","Experimentation","Problem-solving"]

Lead the ML architecture for cross-product search and discovery, focusing on quality, latency, cost, and reliability at scale. Drive technical direction for ranking, retrieval, inference pipelines, and serving infrastructure, using rigorous experimentation to improve search outcomes. Own end-to-end model optimization (quantization, distillation, batching, hardware-aware inference) and enforce ML systems standards with evaluation, shadow traffic, rollout safety, and observability. Mentor senior engineers and partner across teams.

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FursaFursa
Atlassian
Atlassian
1 day ago

Senior Principal Machine Learning Systems Engineer, Search Platform

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Source: Company careers pageValidated by: Fursa AI
Last checked: 13 hours agoStatus: Live

Job Summary

Lead the ML architecture for cross-product search and discovery, focusing on quality, latency, cost, and reliability at scale. Drive technical direction for ranking, retrieval, inference pipelines, and serving infrastructure, using rigorous experimentation to improve search outcomes. Own end-to-end model optimization (quantization, distillation, batching, hardware-aware inference) and enforce ML systems standards with evaluation, shadow traffic, rollout safety, and observability. Mentor senior engineers and partner across teams.
Location: Seattle, San Francisco, Mountain View, New York, Austin
Workplace: Remote
Employment Type: Full time
Job Function: IT Operations (Systems/Network Admin)
Seniority: Sr. Manager level

Key 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 principled engineering.
  • •Identify and pursue high-ambition research moonshots for step-change improvements in search techniques.
  • •Lead end-to-end model optimization, including quantisation, distillation, batching strategies, hardware-aware inference, and latency/accuracy trade-offs.
  • •Define and enforce ML systems standards, including model evaluation, shadow traffic testing, rollout safety, and production observability.

Pay and Benefits

Equity and Bonus:Equity

Key Requirements

  • •12+ years engineering experience with deep expertise in ML systems and production ML infrastructure.
  • •Design and ship low-latency ML serving systems at scale, including ranking, retrieval, or inference pipelines.
  • •Deep expertise in information retrieval and search (dense/sparse retrieval, neural reranking, hybrid search, learning-to-rank).
  • •Experience optimizing models and building large-scale serving infrastructure (Triton, TorchServe, vLLM or equivalent; GPU/CPU; autoscaling).
  • •Strong technical leadership by influencing architecture and decisions across teams/org boundaries.
Experience:Machine learningProduction MLInformation retrievalSearchEnterprise search
Skills:CommunicationTechnical leadershipCross-team collaborationExperimentationProblem-solving
Tech Stack:TritonTorchServeVLLMGPUCPUGCPAWSFedRAMP

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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