3 days ago
Remote, Poland or Gdańsk, PolandSenior
Responsibilities
- Turn product problems into testable ML hypotheses and design experiments against clear baselines.
- Build evaluation datasets and workflows using quantitative metrics and human judgment.
- Develop and improve retrieval, clustering, and language-model pipelines for customer workflows.
- Evaluate trade-offs among quality, latency, cost, and operational complexity, including when fine-tuning is worthwhile.
- Assess performance across customer segments and dataset sizes, including sparse and imbalanced data.
- Take ML capabilities into production with regression checks, monitoring, controlled rollouts, and failure diagnosis.
- Work with product, design, engineering, and platform teams to interpret customer feedback and prioritize improvements.
- Develop reusable evaluation methods and tooling for Product Collection use cases.
Requirements
- Experience delivering applied ML systems beyond prototypes, including product integration, evaluation, monitoring, or post-release improvement.
- Expertise in Python and the ability to write performant, production-quality code.
- Familiarity with SQL, Spark, and cloud data environments such as AWS and Databricks.
- Practical experience in information retrieval, semantic search, natural language processing, clustering, or LLM-based applications.
- Ability to construct useful datasets, select metrics, compare baselines, and investigate offline versus customer-outcome differences.
- Understanding of data leakage, selection bias, imbalanced data, sparse labels, and overfitting.
- Awareness of latency, inference cost, observability, and changing production data.
- Clear communication and collaboration skills across product, design, and engineering disciplines.
- Preferred experience includes retrieval-augmented generation, chunking, embeddings, hybrid search, reranking, text clustering, human evaluation, feedback-based ranking or recommendations, cold-start scenarios, online experiments, model fine-tuning, inference optimization, and reusable ML evaluation or monitoring tooling.
Benefits
- Flexible work arrangement: employees may work from an office, from home, or in a combination of the two.
- The role can be hired in any country where Atlassian has a legal entity.
- Benefits include health and wellbeing resources and paid volunteer days.
- The role may also be eligible for benefits, bonuses, commissions, and equity.
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.