- Experience
- 2+ yrs
- Salary
- —
- Openings
- 1
- Posted
- 1 day ago
- Work mode
- In office
- Resume
- Required to apply
Where you'll work
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Job description
About the Role
Join Atlassian as a Machine Learning System Engineer within the AI & ML Platform team, where you will help develop and enhance the foundational infrastructure that enables countless Atlassian software engineers, ML engineers, and data scientists to build, train, assess, deploy, and manage machine learning models and workflows effectively.
Key Responsibilities
- Work hand-in-hand with product teams like Jira and Confluence to address their unique challenges in implementing ML solutions, including handling datasets and refining both proprietary and open-source large language models (LLMs).
- Lead projects from conceptual design through to implementation and release, collaborating with multiple teams and stakeholders to deliver significant outcomes.
- Participate actively in code reviews, maintain high-quality documentation, deliver bug fixes, and contribute to an engineering culture centered on excellence.
- Mentor less experienced team members and assist in company-wide cross-project engineering initiatives.
Candidate Profile
- Minimum of two years experience in building and maintaining machine learning and AI infrastructure/platforms.
- Comprehensive knowledge across the ML lifecycle including data engineering, model deployment, and operational monitoring.
- Strong expertise in MLOps practices, including the implementation of CI/CD pipelines and automation for ongoing training, deployment, and monitoring.
- Proven ability to design large-scale, resilient, and efficient distributed ML systems.
- Expert proficiency in Python and major ML frameworks such as PyTorch, TensorFlow, or JAX; familiarity with languages like Go, Java, or Scala is advantageous.
- Practical experience with cloud platforms (AWS, GCP, Azure) and their AI/ML offerings, including utilization of GPU resources.
- Experience working with big data and distributed computing frameworks like Spark, Ray, or Dask.
- Strong skills in identifying and resolving performance bottlenecks in ML models and infrastructure.
- Hands-on experience developing generative AI systems, including fine-tuning large language models and building retrieval-augmented generation (RAG) systems.
Compensation and Benefits
Atlassian is committed to fair, transparent, and competitive compensation based on skills, knowledge, and experience. Eligible candidates may also receive benefits, bonuses, commissions, and equity.
The company provides a comprehensive suite of perks including health and wellness resources, paid volunteer opportunities, and community engagement support designed to foster personal and professional growth.
Company Culture and Policies
Atlassian promotes an inclusive workforce that values diversity and prohibits discrimination of any kind. Confidentiality is maintained in accordance with equal employment opportunity standards, and accommodations during recruitment can be requested to ensure an equitable hiring process.
Employment requires identity verification, potentially including biometric data, consistent with local laws for fraud prevention.