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Senior Machine Learning Engineer

AT Atlassian
Atlassian

Senior Machine Learning Engineer

Seattle, WA / Remote

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.

Your Future Team - DevAI

Atlassian's journey began with Jira, a tool designed to help developers track bugs and manage their work. Over the years, Atlassian has expanded its suite of productivity tools, yet developers remain at the heart of our focus. We are revitalizing our product lineup to better serve this core audience. Atlassian's ecosystem uniquely positions us to enhance every step of the developers' productivity cycle. Central to this effort is the creation of a new DevAI pillar, aimed at deeply integrating AI to redefine developer experiences. This includes everything from a daily-use "developer dash" to AI-driven code reviews and autonomous code generation to complete tasks. Our vision is to transform software development, and we have ambitious plans to achieve this.

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What You'll Do

As part of our team, you will play a crucial role in innovating the core intelligence solutions within our DevAI products. Your responsibilities will include (but not limited to) LLM integration, prompt engineering, and developing end-to-end AI features using cutting-edge technologies. You will collaborate closely with a diverse and highly skilled group of scientists and software engineers within our team, as well as with multiple partner teams across the company. Together, we are committed to delivering Atlassian's world-class developer AI products that will shape the future of software development.

General Responsibilities: These are ongoing or overarching tasks that guide the strategic and collaborative aspects of the role:

  • Problem Solving: Identify complex challenges and provide creative solutions to advance the capabilities and functionalities of the products.
  • Collaboration: Work with cross-functional teams, including data scientists and software engineers. Build and maintain sustainable partnerships with team members from various technical backgrounds.
  • Communication: Communicate technical details effectively to the team and engage in technical discussions to contribute ideas and solutions.
  • Continuous Learning: Stay updated with the latest research and advancements in machine learning, AI, and relevant technology applications. Apply cutting-edge knowledge and techniques to enhance product innovation and effectiveness.

Daily Responsibilities: These tasks are more routine or technical, involving hands-on activities that need to be performed regularly:

  • Design and Development: Design LLM based methodology and algorithms tailored to specific product needs.
  • Data Handling: Perform data preprocessing and feature engineering to improve product inputs and performance.
  • Evaluation: Conduct experiments to evaluate the performance of products and use a variety of metrics and testing methods to ensure the solutions meet design specifications.
  • Implementation and Optimization: Implement and optimize machine learning pipelines.
  • Monitoring and Maintenance the deployed intelligence solutions to ensure they continue to perform accurately and efficiently.

Minimum Requirements

  • Bachelor's or Master's degree (preferably a Computer Science degree or equivalent experience)
  • 10+ years of related industry experience and 5+ years of technical expertise in ML and applied science domain.
  • Experience building and scaling machine learning models in business applications using large amounts of data
  • Ability to communicate and explain data science concepts to diverse audiences, craft a compelling story
  • Agile development mindset, appreciating the benefit of constant iteration and improvement

It's great, but not required, if you have

  • Experience in code intelligence space, developer productivity or related fields.
  • Experience working in a consumer or B2C space for a SaaS product provider, or the enterprise/B2B space
  • Experience in developing deep learning-based models and working on LLM-related applications
  • Excelling in solving ambiguous and complex problems, being able to navigate through uncertain situations, breaking down complex challenges into manageable components and developing innovative solutions.

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: $199,400 - $265,800

Zone B: $179,400 - $239,200

Zone C: $165,500 - $220,600

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/perksandbenefitsto 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.

Client-provided location(s): Seattle, WA, USA; San Francisco, CA, USA
Job ID: Atlassian-14908
Employment Type: Full Time

Perks and Benefits

  • Health and Wellness

    • Health Insurance
    • Dental Insurance
    • Vision Insurance
    • Life Insurance
    • Short-Term Disability
    • Long-Term Disability
    • FSA
    • HSA With Employer Contribution
    • Fitness Subsidies
    • Mental Health Benefits
    • On-Site Gym
    • HSA
  • Parental Benefits

    • Adoption Leave
    • Birth Parent or Maternity Leave
    • Non-Birth Parent or Paternity Leave
    • Fertility Benefits
    • Adoption Assistance Program
    • Family Support Resources
  • Work Flexibility

    • Flexible Work Hours
    • Remote Work Opportunities
    • Hybrid Work Opportunities
    • Work-From-Home Stipend
  • Office Life and Perks

    • Holiday Events
    • Casual Dress
    • Pet-friendly Office
    • Happy Hours
    • Snacks
    • Some Meals Provided
    • On-Site Cafeteria
  • Vacation and Time Off

    • Paid Vacation
    • Unlimited Paid Time Off
    • Paid Holidays
    • Personal/Sick Days
    • Volunteer Time Off
    • Sabbatical
    • Leave of Absence
  • Financial and Retirement

    • 401(K) With Company Matching
    • Company Equity
    • Performance Bonus
    • Relocation Assistance
    • Financial Counseling
  • Professional Development

    • Access to Online Courses
    • Internship Program
    • Leadership Training Program
    • Tuition Reimbursement
    • Learning and Development Stipend
    • Promote From Within
  • Diversity and Inclusion

    • Founder led
    • Employee Resource Groups (ERG)
    • Diversity, Equity, and Inclusion Program

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