Note: The job is a remote job and is open to candidates in USA. Atlassian is a software company building collaboration and AI products for teams. The Senior Machine Learning Engineer will develop and productionize machine learning systems for search, retrieval, ranking, conversational experiences, and AI agents, while owning projects across the ML lifecycle. The role also focuses on evaluation-driven development, scalable system design, cross-functional collaboration, and mentoring engineers.
Responsibilities
- Build and productionize machine learning models and AI systems for Search & Intelligence products
- Own projects from concept through deployment, monitoring, evaluation, and iteration
- Develop AI-native experiences across search, retrieval, ranking, recommendations, conversational systems, and agentic workflows
- Design evaluation-driven development processes, including quality metrics, test cases, benchmarks, and acceptance criteria
- Build evaluation datasets, regression suites, and pipelines for search, RAG, chat, and agentic systems
- Conduct offline and online evaluations, human assessments, model-based evaluations, and error analysis
- Design scalable architectures that meet requirements for quality, reliability, latency, privacy, and cost
- Apply modern techniques in information retrieval, ranking, embeddings, NLP, deep learning, and large language models
- Communicate technical decisions and results clearly across technical and non-technical audiences
- Mentor engineers and contribute to engineering and ML best practices
Skills
- A Bachelor's or Master's degree in Computer Science, Machine Learning, Data Science, or a related field, or equivalent experience
- At least 4 years of experience developing and deploying machine learning or AI systems in production
- Strong Python skills and experience with Java, Kotlin, TypeScript, or another production language
- Experience with SQL and large-scale data processing technologies such as Spark
- Experience building, evaluating, deploying, and scaling models with large datasets
- Experience designing evaluation strategies, analyzing model quality, and using results to guide improvements
- Familiarity with cloud-based ML and data platforms such as AWS or Databricks
- Ability to independently solve ambiguous problems and deliver practical, production-quality solutions
- Strong communication and collaboration skills
- An agile mindset and commitment to continuous improvement
- Experience building AI-native products, RAG systems, conversational assistants, or tool-using agents
- Experience with evaluation-driven development, benchmarks, regression testing, human evaluation, or LLM-as-a-judge
- Experience evaluating agent planning, tool use, task completion, or multi-step reasoning
- Experience with search relevance, ranking, recommendations, personalization, embeddings, or NLP
- Experience fine-tuning, post-training, evaluating, or optimizing large language models
- Experience with ML platforms, model serving, data pipelines, observability, or responsible AI
- Experience mentoring engineers or influencing technical direction within a team
Benefits
- Atlassians can choose where they work – whether in an office, from home, or a combination of the two.
- This role may also be eligible for benefits, bonuses, commissions, and equity.
- Health and wellbeing resources
- Paid volunteer days
Company Overview
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