Senior Principal ML Systems Engineer — Search Leader

Atlassian; Seattle (WA); Hybrid; USD 273,000 - 356,000; Full time

Benefits offered by this job

Health benefits

Volunteer days

Perks & benefits

Job summary

At Atlassian, we empower teams to redefine context search and discovery for AI at scale. You will lead ML-based search serving, owning architecture, latency, and reliability while guiding engineers across the org.

You’ll collaborate with product and data teams, drive experiments, and mentor others to raise the technical bar. Our flexible model supports office, home, or hybrid work arrangements.

Qualifications

• 12+ years of engineering experience with ML systems and production ML infrastructure.
• Proven track record shipping low-latency ML serving systems at scale (sub-100ms ranking, retrieval, or inference pipelines).
• Deep expertise in information retrieval and search: dense/sparse retrieval, neural reranking, hybrid search, learning-to-rank.
• Strong command of model optimisation techniques and experience with large-scale serving infrastructure: model serving frameworks, GPU/CPU optimisation, autoscaling.
• Track record of technical leadership without authority - influencing architecture and decisions across team and org boundaries.
• Demonstrated ability to identify high-leverage research directions and drive them from prototype to production.
• Experience with online experimentation and rigorous evaluation frameworks for ML systems.
• Strong communication skills - able to distill complex trade-offs into crisp decisions for technical and non-technical audiences.

Responsibilities

• Set technical direction for ML-based search serving: ranking models, retrieval architectures, inference pipelines, and serving infrastructure
• Drive measurable improvements across search quality, latency, serving cost, and system reliability through rigorous experimentation and principled engineering
• Identify and pursue moonshots — high-ambition, calculated bets on search techniques that deliver step-change improvements
• Lead model optimisation end-to‑end: quantisation, distillation, batching strategies, hardware‑aware inference, and latency/accuracy trade‑offs
• Define and enforce ML systems standards: model evaluation, shadow traffic testing, rollout safety, and production observability
• Mentor and elevate senior engineers across Search Serving; raise the technical bar through design reviews, architecture decisions, and hands‑on guidance
• Partner across teams - Search Quality, ML Platform, and product - to align roadmaps and unblock high‑impact work
• Translate ambiguous problems into clear technical bets with measurable success criteria

Skills

Low-latency ML serving

Information retrieval

ML systems design

Model optimisation

Online experimentation

Technical leadership without authority

Communication skills

Tools

Triton

TorchServe

vLLM

Job description

At Atlassian, we empower teams to redefine context search and discovery for AI at scale. You will lead ML-based search serving, owning architecture, latency, and reliability while guiding engineers across the org.

You’ll collaborate with product and data teams, drive experiments, and mentor others to raise the technical bar. Our flexible model supports office, home, or hybrid work arrangements.