> Markdown version of [/jobs/ext/3973426-senior-machine-learning-engineer-ai-native-evaluation-search](https://www.wearedevelopers.com/jobs/ext/3973426-senior-machine-learning-engineer-ai-native-evaluation-search). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Machine Learning Engineer, AI-Native Evaluation & Search - **Company:** Atlassian - **Location:** San Francisco, CA, United States - **Experience:** Expert - **Salary:** $206,100.0 - $269,075.0 - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Artificial Intelligence, Amazon Web Services, Big Data, Cloud Computing, Database Development, Information Retrieval, Python (Programming Language), Machine Learning, Natural Language Processing, Regression Testing, Azure Machine Learning, SQL Databases, TypeScript, Retrieval-Augmented Generation, Large Language Models, Apache Spark, Deep Learning, Agentic-AI, Kotlin, Information Technology, Low Latency, Atlassian Tools, Data Management, Machine Learning Operations, Data Pipelines, Databricks - **Published:** October 27, 2026 - **Apply:** https://www.careerbuilder.com/job-details/senior-machine-learning-engineer-ai-native-evaluation-search-san-francisco-ca--f1d8188b-0b62-497e-ac13-5cb8b80d022a ## About the Role Machine Learning, Artificial Intelligence (AI), Intelligence Agencies, Artificial Intelligence (AI), Machine Learning, Legal, Continuous Improvement, Artificial Intelligence (AI) Agents, Production Machining, Production Systems, On your first day, we'll expect you to have * 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. It's great, but not required, if you have * 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. ## Description Atlassian is looking for a Senior Machine Learning Engineer to join our Search & Intelligence organization. We build AI-native experiences, agentic systems, models, evaluation frameworks, and data platforms that power Atlassian's AI products. 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 You will develop and productionize machine learning systems for search, retrieval, ranking, conversational experiences, and AI agents. You will own projects across the ML lifecycle, from problem definition and data development through experimentation, evaluation, deployment, and continuous improvement. A key part of this role is making evaluation a first-class part of AI development. You will help define quality, build evaluation datasets and benchmarks, analyze model behavior, and use results to guide product and engineering decisions. You will collaborate with product managers, software engineers, data scientists, research scientists, and platform teams. You will independently solve complex problems, contribute to technical direction, and mentor other engineers. What you'll do * 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.