Senior Machine Learning System Engineer

Posted 3 Hours Ago
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Hiring Remotely in Seattle, WA, USA
In-Office or Remote
149K-235K Annually
Senior level
Cloud • Information Technology • Productivity • Security • Software • App development • Automation
Atlassian provides tools to help every team unleash their full potential.
The Role
Design, build, and operate scalable, low-latency search and retrieval systems powering Atlassian products. Develop and serve production ML models (neural rankers, embeddings, rerankers) using PyTorch and Triton. Implement vector indexing and RAG/agentic retrieval pipelines, ensure observability and cost optimization, manage on-call/runbooks, and collaborate cross-functionally while mentoring junior engineers.
Summary Generated by Built In
Working at Atlassian
Atlassians can choose where they work - whether in an office, from home, or a combination of the two. That way, Atlassians have more control over supporting their family, personal goals, and other priorities. We can hire people in any country where we have a legal entity.
As a senior Machine Learning Systems Engineer on the Search Platform team, you will own and drive the design, development, and production deployment of machine learning systems that power search experiences across Atlassian's product suite, including Jira, Confluence, and Rovo.
Search Platform Engineering Design and implement scalable search serving infrastructure, including retrieval pipelines, vector indexing systems, and embedding-based semantic search. Own end-to-end delivery of ML components from experimentation through production rollout across multiple regions and tenants. Contribute to the architecture of high-throughput, low-latency search systems that meet strict SLO targets for availability, latency, and relevance quality.
ML Model Development & Serving Build and maintain production ML models including neural rankers, embedding models, and reranking systems. Integrate models into serving infrastructure using frameworks such as Triton and PyTorch, ensuring reliability, scalability, and cost efficiency. Collaborate with ML researchers to translate experimental models into production-grade systems with robust monitoring and evaluation harnesses.
Agentic Search & Retrieval Design retrieval systems purpose-built for agentic and RAG (Retrieval-Augmented Generation) use cases, including personalized indexes, grounding pipelines, and multi-step retrieval workflows. Partner with Rovo and AI platform teams to evolve search infrastructure as a foundational layer for AI agents, ensuring retrieval quality, freshness, and relevance at scale.
Operational Excellence & Cost Discipline Drive observability, monitoring, and incident response for search serving systems. Apply FinOps principles to identify and execute cost optimization opportunities across vector search infrastructure and ML serving fleets. Maintain production health through rigorous on-call practices, runbook development, and proactive capacity planning.
Cross-Functional Collaboration Work closely with engineering leads, product managers, and platform stakeholders to define technical roadmaps and deliver against team OKRs. Mentor junior engineers, contribute to design reviews, and champion engineering best practices across the team.
At Atlassian, we strive to design equitable, explainable, and competitive compensation programs. We follow consistent hiring practices and account for each candidate's skills, knowledge, and experience when setting base pay within the range.
Please visit go.atlassian.com/payzones for more information on which locations are included in each of our geographic pay zones. However, please confirm the zone for your specific location with your recruiter.
This role may also be eligible for benefits, bonuses, commissions, and equity.
In The United States, we have three geographic pay zones. For this role, our current base pay ranges for new hires in each zone are:
Zone A: $180,000 - $235,000
Zone B: $162,000 - $211,500
Zone C: $149,400 - $195,050
Benefits & Perks
Atlassian 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 go.atlassian.com/perksandbenefits .
About Atlassian
At Atlassian, we're motivated by a common goal: to unleash the potential of every team. Our software products help teams all over the planet and our solutions are designed for all types of work. Team collaboration through our tools makes what may be impossible alone, possible together.
We believe that the unique contributions of all Atlassians create our success. To ensure that our products and culture continue to incorporate everyone's perspectives and experience, we never discriminate based on race, religion, national origin, gender identity or expression, sexual orientation, age, or marital, veteran, or disability status. All your information will be kept confidential according to EEO guidelines.
To provide you the best experience, we can support with accommodations or adjustments at any stage of the recruitment process. Simply inform our Recruitment team during your conversation with them.
To learn more about our culture and hiring process, visit go.atlassian.com/crh .
In line with local law, identity verification (which may include use of biometric data) is a condition of employment with Atlassian for employment fraud purposes.

Skills Required

  • Design and implement scalable search serving infrastructure including retrieval pipelines and vector indexing systems
  • Experience building and maintaining production ML models (neural rankers, embedding models, reranking systems)
  • Integrate models into serving infrastructure using Triton and PyTorch
  • Design retrieval systems for agentic search and RAG use cases, including personalized indexes and grounding pipelines
  • Deliver end-to-end ML components from experimentation to multi-region, multi-tenant production rollout meeting SLOs
  • Operate production systems with strong observability, monitoring, incident response, runbooks, and on-call responsibility
  • Apply FinOps/cost-optimization principles across vector search infrastructure and ML serving fleets
  • Collaborate with ML researchers to productionize experimental models and build evaluation/monitoring harnesses
  • Mentor junior engineers and participate in design reviews, roadmap planning, and cross-functional collaboration

What the Team is Saying

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Atlassian Compensation & Benefits Highlights

  • Parental & Family Support Parental leave is described as generous for both birthing and non‑birthing parents, with inclusive family‑formation coverage spanning fertility, adoption, and surrogacy. Additional caregiving resources such as breastmilk shipping and neurodiverse family support reinforce a family‑first approach.
  • Healthcare Strength Health coverage is characterized as comprehensive, pairing major medical plans with extensive mental‑health services. Benefits also include support for abortion travel, transgender care, and complex mental‑health needs.
  • Leave & Time Off Breadth Time off is framed as flexible, with ample PTO, multiple leave programs, and five paid volunteer days annually. Sabbaticals and donation matching add further headroom for rest and purpose.

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The Company
HQ: San Francisco, CA
11,000 Employees
Year Founded: 2012

What We Do

Atlassian creates teamwork solutions for high-performing teams. Our portfolio of collaboration and work management software products includes Jira, Confluence, Trello, Loom and Rovo. More than 300,000 businesses worldwide rely on Atlassian’s technology, including 80 percent of Fortune 500 companies. Our solutions support various business teams and they help organizations plan, track, and deliver their biggest ideas together.

Why Work With Us

At Atlassian, we believe we can accomplish so much more together than apart — which is why everything from our tooling — to our distributed workforce — to how our teams are structured is rooted in collaboration. Come join us and help unleash the potential of every team.

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Atlassians have flexibility in where they work to support their family, personal goals, and other priorities. Our approach to distributed work allows us to tap into talent beyond our office locations, and to reimagine how work gets done.

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