Machine Learning Engineer

About The Company

Atlassian Corp. is a leading provider of collaborative software solutions designed to empower teams worldwide. Our mission is to unleash the potential of every team by creating tools that facilitate seamless communication, project management, and workflow automation. With a diverse portfolio of products such as Jira, Confluence, Trello, and Bitbucket, we enable organizations of all sizes to work more efficiently and effectively. Our commitment to innovation, inclusivity, and continuous improvement drives us to develop solutions that address the evolving needs of modern workplaces.

As a globally distributed company, Atlassian values flexibility and inclusivity, allowing employees to work from anywhere—whether in an office, remotely, or a hybrid setup. We foster a culture of collaboration, transparency, and respect, ensuring every team member's contributions are recognized and valued. Our dedication to social responsibility is reflected in our initiatives supporting community engagement, diversity, and sustainability.

About The Role

We are seeking a highly skilled Senior Machine Learning Engineer to join our Confluence Cloud AI team. This role offers a unique opportunity to work on cutting-edge machine learning solutions that directly impact our revenue streams, user engagement, and strategic forecasting capabilities. The ideal candidate will be responsible for designing, developing, and deploying advanced machine learning models, particularly focusing on forecasting and predictive analytics, to support business decisions and growth initiatives.

The Senior Machine Learning Engineer will collaborate closely with cross-functional teams—including Growth, Product, Sales, Finance, and Engineering—to translate complex business challenges into scalable, data-driven solutions. This position involves leading the entire machine learning lifecycle, from problem definition and data preparation to experimentation, deployment, and continuous improvement. The role demands a combination of technical expertise, strategic thinking, and effective communication skills to explain complex concepts to both technical and non-technical stakeholders.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, or a related field. A Ph.D. is a plus.
• Extensive experience in developing and deploying machine learning models in a production environment.
• Proficiency in programming languages such as Python, Java, or Scala, with experience using machine learning frameworks like TensorFlow, PyTorch, or scikit-learn.
• Strong understanding of statistical analysis, data modeling, and algorithm development.
• Experience with large-scale data processing and cloud computing platforms such as AWS, GCP, or Azure.
• Excellent problem-solving skills and the ability to translate business needs into technical solutions.
• Proven ability to lead projects, mentor junior team members, and communicate complex technical concepts effectively.
• Experience working in an agile environment and familiarity with DevOps practices for machine learning deployment.

Responsibilities

• Drive the development and implementation of sophisticated machine learning algorithms to address critical business challenges.
• Design scalable, reliable, and high-performance forecasting models, including deep learning-based approaches, to predict company top-line metrics at granular levels.
• Lead the end-to-end machine learning lifecycle, encompassing problem formulation, data collection and cleaning, feature engineering, model training, evaluation, and deployment.
• Architect and develop system and model architectures that support robust, scalable, and production-ready solutions.
• Establish rigorous model evaluation and validation procedures, leveraging data-driven insights to enhance model accuracy and business impact.
• Collaborate with cross-functional teams to understand complex business problems and translate them into effective machine learning solutions.
• Build and improve machine learning infrastructure, including pipelines, APIs, and tools that facilitate continuous model iteration and deployment.
• Communicate technical concepts and findings clearly to both technical and non-technical audiences, ensuring alignment and understanding across teams.
• Provide mentorship and technical guidance to junior engineers, fostering a culture of learning and innovation.
• Balance the need for high-quality, accurate models with practical considerations such as deployment speed and business requirements.

Benefits

At Atlassian, we offer a comprehensive benefits package designed to support your health, wellbeing, and professional growth. Our offerings include competitive health insurance plans, wellness resources, paid time off, and flexible work arrangements to promote work-life balance. We provide opportunities for continuous learning through training programs, conferences, and skill development initiatives. Additionally, employees can participate in volunteer days and community engagement activities that foster a sense of purpose and connection. Our compensation programs are designed to be equitable and competitive, reflecting your skills and experience. Eligible employees may also receive bonuses, stock options, and other incentives to reward their contributions.

Equal Opportunity

At Atlassian, we are committed to fostering an inclusive environment where everyone feels valued and respected. We do not discriminate based on race, religion, national origin, gender identity or expression, sexual orientation, age, marital status, veteran status, disability, or any other protected characteristic. Our hiring practices are transparent and equitable, ensuring that all candidates are evaluated based on their skills, knowledge, and experience. We support accommodations and adjustments at any stage of the recruitment process to provide a fair opportunity for all applicants. We believe that diverse teams drive innovation and success, and we are dedicated to creating a workplace that reflects the communities we serve.