Base Salary
$171k - $269k/yr
Responsibilities
- Lead the design, development, implementation, and productionization of machine learning algorithms, models, and systems.
- Own machine learning projects from concept through deployment, measurement, optimization, and continuous improvement.
- Develop scalable data and modeling approaches using large and complex datasets.
- Design system and model architectures meeting quality, latency, scale, reliability, privacy, and cost requirements.
- Build machine learning solutions for information retrieval, search ranking, personalization, natural language processing, deep learning, and large language model applications.
- Design and execute offline evaluations, online tests, experiments, metrics strategies, and error analyses.
- Collaborate with product, engineering, analytics, data science, and platform teams to integrate AI capabilities into products and services.
- Translate emerging AI techniques into reliable, maintainable, production-quality systems.
- Communicate technical decisions, trade-offs, results, and recommendations to technical and non-technical audiences.
- Mentor machine learning engineers and contribute to technical strategy and organizational best practices.
Requirements
- 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 SQL knowledge and experience 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 or Databricks.
- Experience using metrics, experimentation, evaluation strategies, and error analysis to improve models and products.
- Preferred qualifications include experience with search, recommendations, ranking, personalization, NLP, deep learning, LLMs, agentic systems, ML platforms, model serving, feature stores, data pipelines, observability, or responsible AI.
- Preferred qualifications also include technical leadership, architecture and strategy influence, mentoring, and experience in consumer, SaaS, or enterprise B2B environments.
Benefits
- Flexible work arrangement with the option to work from an office, from home, or a combination of both, subject to locations where Atlassian has a legal entity.
- Benefits may include health and wellbeing resources, paid volunteer days, bonuses, commissions, and equity.
- Workplace accommodations and adjustments are available throughout the recruitment process.
Tech Stack
Categories
About Atlassian
Atlassian powers the collaboration that helps teams accomplish what would otherwise be impossible alone. From space missions and motor racing to bugs in code and IT requests, no task is too large or too small with the right team, the right tools, and the right practices. Over 300,000 global companies and 80% of the Fortune 500 rely on Atlassian’s software, like Jira, Confluence, Loom, and Trello, to help their teams work better together and deliver quality results on time. With our 300,000+ customers and team of 10,000+ Atlassians, we are building the next generation of team collaboration and productivity software. We believe the power of teams has the potential to change the world — one that is more open, authentic, and inclusive.