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Machine Learning Systems Engineer

Overview

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. Interviews and onboarding are conducted virtually, a part of being a distributed-first company.

About Central AI Org

Our organisation is designed to accelerate AI innovation across all our products and platform, provide cohesive AI experiences and setup up an Atlassian AI infrastructure for the future. Our purpose is to:

  • Build horizontal AI capabilities and infrastructure which provides leverage across products

  • Build a centralised Search, Q&A and Conversational AI across all Atlassian products.

  • Explore integration of Atlassian products with AI products outside Atlassian.

  • About AI & ML Platform Team

    Our team is building the foundations to democratise Machine Learning for Atlassian's teams, customers and ecosystem. Our goal is to create tools that are user-friendly and reliable, ensuring that Atlassian teams can easily embrace and utilize them. These tools will facilitate the development, deployment, measurement, and operation of AI & ML experiences. They will seamlessly integrate with the Atlassian Data Platform, enabling teams to efficiently and rapidly incorporate AI & ML capabilities into their workflows. The focus is on providing a smooth and hassle-free experience for Atlassian users, allowing them to leverage the power of AI & ML without any complications.

    Responsibilities

    As a Senior Engineer on the AI & ML Platform team, you will build and scale the core infrastructure to allow software engineers, ML engineers & data scientists to develop, train, evaluate, deploy, and operate Machine Learning models and pipelines. Along with that, you will build systems for product teams like Jira & Confluence to provide access to curated LLMs. You will use your software development expertise to solve difficult problems, tackling infrastructure and architecture challenges.

    You will have the opportunity to lead engineers to drive involved projects from technical design to launch. You will also collaborate with other teams and internal customers to set expectations, gather input and communicate results.

    In this role, you'll get the chance to:

    • Regularly tackle complex problems in the team, from technical design to launch.

    • Routinely tackle complex architecture challenges and defines coding standards & patterns for the team.

    • Lead the team through times of ambiguity, help them adapt and and deliver positive impact.

    • Mentor junior members on the team.

    Our tech stack is primarily Java/Kotlin built on AWS.

    Qualifications

    • Fluency in at least one modern object-oriented programming language (preferably Java/Kotlin).

    • Understanding and experience with Machine Learning project lifecycle and tools.

    • Understanding of LLMs, best deployment practices and inference optimisation.

    • Experience in building and implementing high-performance RESTful micro-services.

    • Experience building and operating large scale distributed systems using Amazon Web Services (Sagemaker, S3, Cloud Formation, AWS Security and Networking).

    • Experience with Continuous Delivery and Continuous Integration.

    Compensation

    At Atlassian, we strive to design equitable, explainable, and competitive compensation programs. To support this goal, the baseline of our range is higher than that of the typical market range, but in turn we expect to hire most candidates near this baseline. Base pay within the range is ultimately determined by a candidate's skills, expertise, or experience. 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: $176,200 - $235,000

    Zone B: $158,600 - $211,500

    Zone C: $146,300 - $195,000

    This role may also be eligible for benefits, bonuses, commissions, and equity.

    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.

    Our perks & benefits

    Atlassian offers a variety of perks and benefits to support you, your family and to help you engage with your local community. Our offerings include health coverage, paid volunteer days, wellness resources, and so much more. Visit go.atlassian.com/perksandbenefits to learn more.

    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.

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    Average salary estimate

    $190650 / YEARLY (est.)
    min
    max
    $146300K
    $235000K

    If an employer mentions a salary or salary range on their job, we display it as an "Employer Estimate". If a job has no salary data, Rise displays an estimate if available.

    What You Should Know About Machine Learning Systems Engineer, Atlassian

    At Atlassian, we are excited to invite applications for the role of Machine Learning Systems Engineer in our vibrant San Francisco office! In this pivotal position, you will be joining the AI & ML Platform team, dedicated to democratizing machine learning for our teams and customers. Imagine being the backbone that enables software engineers, machine learning engineers, and data scientists to create, train, and deploy models with ease. You'll be leveraging your expertise to solve complex infrastructure challenges while ensuring the smooth operation of AI integrations across our beloved products like Jira and Confluence. Collaboration is at the heart of what we do, and in this role, you will engage with cross-functional teams to define coding standards and guide the engineering team through complex design projects. If you are passionate about seamlessly integrating AI into workflows and mentoring budding engineers, then this is the perfect opportunity for you! Our tech stack is primarily Java/Kotlin on AWS, and your experience in high-performance RESTful microservices will be invaluable. Join us in making modern software products intuitive and powerful for all teams across the globe by applying for the Machine Learning Systems Engineer role today!

    Frequently Asked Questions (FAQs) for Machine Learning Systems Engineer Role at Atlassian
    What responsibilities does the Machine Learning Systems Engineer at Atlassian have?

    The responsibilities of the Machine Learning Systems Engineer at Atlassian include building and scaling core infrastructure to enable software engineers, ML engineers, and data scientists to develop, train, evaluate, deploy, and operate machine learning models and pipelines. The engineer will also create systems for teams like Jira and Confluence to access curated LLMs while resolving complex architecture challenges and mentoring junior engineers.

    Join Rise to see the full answer
    What qualifications do I need to apply for the Machine Learning Systems Engineer position at Atlassian?

    To apply for the Machine Learning Systems Engineer position at Atlassian, candidates should be fluent in at least one modern object-oriented programming language, preferably Java or Kotlin. A solid understanding of the machine learning project lifecycle, experience with high-performance RESTful microservices, and familiarity with AWS tools are also essential qualifications for this role.

    Join Rise to see the full answer
    What tech stack is used by the Machine Learning Systems Engineer team at Atlassian?

    The tech stack used by the Machine Learning Systems Engineer team at Atlassian primarily revolves around Java and Kotlin, built on Amazon Web Services (AWS). This stack supports the development, deployment, and operation of machine learning models and enables integration with various AI capabilities across Atlassian products.

    Join Rise to see the full answer
    What kind of projects can I expect to work on as a Machine Learning Systems Engineer at Atlassian?

    As a Machine Learning Systems Engineer at Atlassian, you can expect to work on various projects that tackle complex infrastructure and architecture challenges. These projects include building systems for product teams to leverage machine learning capabilities and enhancing the user experience by integrating AI technologies into Atlassian's suite of products.

    Join Rise to see the full answer
    What opportunities for growth does Atlassian offer for Machine Learning Systems Engineers?

    At Atlassian, Machine Learning Systems Engineers have plenty of opportunities for growth, including the chance to mentor junior team members and lead complex projects from design to launch. The collaborative environment and focus on innovative AI solutions also allow engineers to expand their skills and explore new technologies.

    Join Rise to see the full answer
    Common Interview Questions for Machine Learning Systems Engineer
    Can you describe a challenging project you worked on as a Machine Learning Systems Engineer?

    To effectively answer this question, select a project where you faced significant challenges and describe your approach to solving them. Emphasize your problem-solving skills, technical expertise, collaboration with team members, and the positive impact the project had on the organization's goals.

    Join Rise to see the full answer
    How do you approach the deployment of machine learning models in production?

    Discuss your understanding of the machine learning project lifecycle and detail your experience with best practices for deploying models, including version control, testing, CI/CD pipelines, and monitoring performance post-deployment to ensure reliability and adaptability.

    Join Rise to see the full answer
    What tools do you prefer for developing and training machine learning models?

    Share your preferred tools and frameworks, such as TensorFlow or PyTorch, and explain why you choose them. Highlight any specific projects you've completed using these tools, focusing on how they aided in achieving your project goals effectively.

    Join Rise to see the full answer
    How do you ensure high performance in your machine learning systems?

    Explain your strategy for optimizing the performance of machine learning systems, which may include techniques like model selection, hyperparameter tuning, and efficient use of AWS resources. Provide examples of how these practices led to improved performance in past projects.

    Join Rise to see the full answer
    Describe your experience with distributed systems and AWS services.

    Detail your experiences with building and operating large-scale distributed systems on AWS, such as using S3 for storage or SageMaker for model training. Mention specific challenges you faced and how you overcame them by leveraging AWS services effectively.

    Join Rise to see the full answer
    What is your experience with mentoring junior engineers?

    Discuss your involvement in mentoring or training junior engineers, emphasizing how you helped them grow their skills. Provide specific examples of mentoring activities you undertook, such as code reviews, knowledge-sharing sessions, or leading discussions on best practices.

    Join Rise to see the full answer
    How do you stay updated with the latest developments in machine learning?

    Talk about the resources you use to stay informed, such as attending conferences, participating in workshops, or taking online courses. Mention any influential publications, blogs, or communities you are part of that focus on AI and machine learning advancements.

    Join Rise to see the full answer
    Can you explain how you handle ambiguity in projects?

    Share your approach to dealing with ambiguity, such as breaking down complex problems into manageable parts, collaborating with team members for clarity, and iterating on designs based on feedback. Emphasize adaptability and open communication as key strategies.

    Join Rise to see the full answer
    What is your understanding of LLMs and their application in products?

    Demonstrate your knowledge of Large Language Models (LLMs), their importance in modern applications, and how you have integrated or plan to integrate them into product features. Discuss their deployment practices and optimization techniques.

    Join Rise to see the full answer
    How would you define coding standards and patterns for a team?

    Explain your philosophy about coding standards, emphasizing the importance of maintainable and readable code. Discuss how you would advocate for best practices within the team and create documentation to support these standards.

    Join Rise to see the full answer
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    CULTURE VALUES
    Customer-Centric
    Empathetic
    Collaboration over Competition
    Feedback Forward
    Inclusive & Diverse
    Mission Driven
    Diversity of Opinions
    Rise from Within
    BENEFITS & PERKS
    Medical Insurance
    Paid Time-Off
    Dental Insurance
    Vision Insurance
    Maternity Leave
    Mental Health Resources
    Equity
    401K Matching
    Employee Resource Groups
    Performance Bonus
    Education Stipend
    Life insurance
    FUNDING
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    EMPLOYMENT TYPE
    Full-time, remote
    DATE POSTED
    March 28, 2025

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