NextRaiseNextRaiseFind jobs
Sign inSign up free
Jobs / Machine Learning Engineer in United States of America
16 days ago
Apply with autofill
Apply with autofill
Atlassian·SaaS·16 days ago
16 days ago

Principal Machine Learning Engineer

San Francisco, United States of AmericaFull-timeRemoteSenior · 10-15 yearsMachine Learning Engineer

Sign up free to see how well your resume matches this role.

Boost your chances at Atlassian

How you compare FREE

?
Your scoreYour score: not yet known
→
67
Top 10%Top 10%: 67 out of 100

Top 10% of NextRaise users matched against Machine Learning Engineer roles in United States.

Must-have skills for this role

  • machine learning
  • artificial intelligence
  • production engineering
  • experimentation

PDF or DOCX · no account needed

Apply faster with autofill FREEThe NextRaise extension autofills your application in one click.careers.example.com/applyAutofillingFull namePriya SharmaEmailpriya.sharma@example.comPhone+49 30 1234567LocationBerlGet the extension

What you'll do

  • Set technical direction for machine learning and AI initiatives that power Confluence experiences across areas such as content creation, editing, summarization, recommendations, and multimodal interaction.
  • Design, build, and evolve production-grade ML systems, evaluation workflows, experimentation loops, and supporting infrastructure that enable reliable delivery of AI features at scale.
  • Lead the development of customer-facing AI capabilities by translating ambiguous product opportunities into practical technical strategies, measurable outcomes, and shipped experiences.
  • Drive advances in areas such as model behavior, retrieval, ranking, prompt and workflow design, automated evaluation, quality measurement, and system reliability.
  • Partner closely with engineering, product, design, analytics, and platform teams to align on priorities, influence roadmaps, and deliver cross-organizational initiatives.
  • Identify systemic product or model failure modes, develop interventions, and close the loop between technical improvements and customer impact through experimentation and data-driven iteration.
  • Make high-leverage architectural decisions across application layers, balancing model quality, latency, cost, safety, maintainability, and user experience.
  • Contribute as a deeply hands-on engineer when needed, including prototyping, implementation, debugging, and guiding complex production rollouts.
  • Raise the bar for principal-level engineering by mentoring other engineers, leading design reviews, improving technical quality, and establishing reusable patterns that benefit multiple teams.
  • Help build the foundations that allow Confluence AI teams to ship deeper, more integrated AI experiences across editor surfaces, content types, and collaborative workflows.

Summarised by NextRaise from the employer’s description, which follows in full below.

Full description from employer

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 Principal Machine Learning Engineer in the Confluence AI organization, you will help shape the next generation of AI-powered experiences across Confluence. This is a hands-on principal-level role for an engineer who can turn fast-moving advances in machine learning into high-quality product experiences that reach customers at scale.

You will work across product, platform, and partner teams to define technical direction, solve ambiguous problems, and deliver AI capabilities that improve how users create, edit, discover, and interact with content. The role spans the full stack of AI product development, from model-informed product design and evaluation strategy to production engineering, experimentation, and long-term technical leadership.

This role is especially well suited for someone who combines strong machine learning depth with product instinct and systems thinking. Success in this position means not only building sophisticated AI systems, but also identifying the highest-value opportunities, raising engineering standards, and helping multiple teams move faster and with more confidence.

Responsibilities:

  • Set technical direction for machine learning and AI initiatives that power Confluence experiences across areas such as content creation, editing, summarization, recommendations, and multimodal interaction.

  • Design, build, and evolve production-grade ML systems, evaluation workflows, experimentation loops, and supporting infrastructure that enable reliable delivery of AI features at scale.

  • Lead the development of customer-facing AI capabilities by translating ambiguous product opportunities into practical technical strategies, measurable outcomes, and shipped experiences.

  • Drive advances in areas such as model behavior, retrieval, ranking, prompt and workflow design, automated evaluation, quality measurement, and system reliability.

  • Partner closely with engineering, product, design, analytics, and platform teams to align on priorities, influence roadmaps, and deliver cross-organizational initiatives.

  • Identify systemic product or model failure modes, develop interventions, and close the loop between technical improvements and customer impact through experimentation and data-driven iteration.

  • Make high-leverage architectural decisions across application layers, balancing model quality, latency, cost, safety, maintainability, and user experience.

  • Contribute as a deeply hands-on engineer when needed, including prototyping, implementation, debugging, and guiding complex production rollouts.

  • Raise the bar for principal-level engineering by mentoring other engineers, leading design reviews, improving technical quality, and establishing reusable patterns that benefit multiple teams.

  • Help build the foundations that allow Confluence AI teams to ship deeper, more integrated AI experiences across editor surfaces, content types, and collaborative workflows.

Qualifications:

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 or Remote, we have three geographic pay zones. For this role, our current base pay ranges for new hires in each zone are:

Zone A: $236,700 - $309,025

Zone B: $213,030 - $278,123

Zone C: $196,461 - $256,491

SaaS

Company

AtlassianSaaS
San Francisco, United States of America

Company facts come from this company's own listings. We only show what the postings themselves carry.

Sourced from Atlassian's careers site·first seen 14 Sept 2026·last verified 18 Sept 2026·How we source jobs

Similar jobs

  • Senior Machine Learning Data Scientist at OuraRemote - United States–match not yet calculated
  • Machine Learning Engineer at zenosSan Mateo Werqwise, United States of America–match not yet calculated
  • Senior Machine Learning Engineer, AI Platform & Agentic Apps at RobinhoodMenlo Park, United States of America–match not yet calculated
  • Machine Learning Engineer II at ChewyRichardson, United States of America–match not yet calculated
  • Senior Machine Learning Engineer, AI Infra at RobinhoodBellevue, United States of America–match not yet calculated

Browse more jobs

  • Machine Learning Engineer jobs in United States
  • AI / ML Researcher jobs in United States
  • AI Engineer jobs in United States
  • Computer Vision Engineer jobs in United States
  • Machine Learning Engineer jobs in India
  • Machine Learning Engineer jobs in United Kingdom