Senior Machine Learning Engineer, Search & Intelligence

Overview

Atlassian is looking for a Senior Machine Learning Engineer to join our Search & Intelligence organization. Our team builds the intelligent experiences, agentic systems, models, evaluation frameworks, and data pipelines that power Atlassian’s AI products and accelerate AI innovation across the company.

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.

Responsibilities

Your role and impact

As a Senior Machine Learning Engineer, you will lead the development and productionization of advanced machine learning systems that improve how people discover, understand, and act on knowledge across Atlassian. You will work across the full machine learning lifecycle, from problem definition and data exploration to model development, experimentation, evaluation, deployment, and ongoing optimization.

You will partner closely with product managers, software engineers, data scientists, and other technical stakeholders to translate ambiguous product challenges into scalable AI solutions. You will contribute to architectural decisions, raise engineering and scientific standards, and mentor other machine learning engineers.

Your work will help deliver intelligent search, recommendations, conversational experiences, and other AI capabilities used by Atlassian customers worldwide.

What you’ll do

• Lead the design, development, and implementation of state-of-the-art machine learning algorithms and models for production environments.

• Own machine learning projects from initial concept through production deployment, measurement, and continuous improvement.

• Develop scalable data and modeling approaches using large, complex datasets.

• Design robust system and model architectures that meet requirements for quality, latency, scale, reliability, privacy, and cost.

• Build and improve machine learning solutions across areas such as information retrieval, search ranking, personalization, natural language processing, deep learning, and large language model applications.

• Design and execute rigorous experiments, offline evaluations, online tests, and error analyses to measure model quality and product impact.

• Collaborate with product, engineering, data science, analytics, and platform teams to integrate AI capabilities into Atlassian products and services.

• Translate research and emerging AI techniques into reliable, maintainable, production-quality systems.

• Identify opportunities to improve model performance, operational efficiency, developer experience, and customer outcomes.

• Communicate technical decisions, trade-offs, results, and recommendations clearly to both technical and non-technical audiences.

• Mentor and support machine learning engineers, contribute to technical strategy, and help establish best practices across the organization.

• Contribute to a culture of experimentation, continuous learning, inclusive collaboration, and iterative delivery.

Compensation

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.

Pay Ranges

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: $206,100 - $269,075

Zone B: $185,490 - $242,168

Zone C: $171,063 - $223,332

Qualifications

On your first day, we’ll expect you to have

• A Bachelor’s or Master’s degree in Computer Science, Machine Learning, Artificial Intelligence, Data Science, or a related field, or equivalent practical experience.

• At least 5 years of professional experience developing and deploying machine learning or data science solutions in production.

• Strong programming skills in Python and one or more production languages such as Java, Kotlin, or TypeScript.

• Strong knowledge of SQL and experience working with large-scale data processing technologies such as Spark.

• Experience designing, training, evaluating, deploying, and scaling machine learning models using large and complex datasets.

• Experience building performant, reliable, and maintainable production-quality software.

• Familiarity with cloud-based data and machine learning environments, such as AWS, Databricks, or comparable platforms.

• Experience designing evaluation strategies and using metrics, experimentation, and error analysis to guide model and product improvements.

• Experience collaborating effectively across product, engineering, analytics, and data science teams.

• An ability to independently navigate ambiguous and complex problems, break them into manageable components, and deliver practical solutions.

• Strong written and verbal communication skills, with the ability to explain complex technical concepts clearly.

• An agile development mindset and an appreciation for rapid iteration, continuous improvement, and learning from results.

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

• End-to-end experience integrating machine learning or AI capabilities into customer-facing products.

• Experience building search, recommendation, ranking, personalization, or natural language processing systems.

• Experience developing deep learning models and applying large language models to production use cases.

• Experience with agentic systems, tool-using models, or multi-step reasoning and planning systems.

• Experience fine-tuning, evaluating, monitoring, and optimizing large language models.

• Experience working in a consumer or B2C environment, a SaaS product organization, or an enterprise B2B environment.

• Experience with ML platforms, model serving, feature stores, data pipelines, observability, or responsible AI practices.

• A track record of technical leadership, influencing architecture and strategy beyond your immediate team, and mentoring other engineers.

• Experience balancing long-term technical investments with pragmatic delivery in an evolving product environment.

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.