Senior Machine Learning Engineer

March 26

🏄 California – Remote

Although this job is listed in California, this company may be open to hiring remote in other states.

💵 $146.3k - $235k / year

⏰ Full Time

🟠 Senior

🤖 Machine Learning Engineer

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Atlassian

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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.

b2b enterprise software • bug tracker • issue tracker • enterprise wiki • corporate wiki

10,000+ employees

💰 $3.2G Secondary Market on 2014-04

📋 Description

• Work on the development and implementation of cutting-edge machine learning algorithms • Train sophisticated models, collaborating with product, engineering, and analytics teams • Build AI functionalities into each Atlassian product and service • Design system and model architectures • Conduct rigorous experimentation and model evaluations • Provide guidance to junior ML engineers • Ensure AI's transformative potential is realized across our offerings

🎯 Requirements

• Master or PhD in a quantitative subject (Statistics, Mathematics, Computer Science, Operations Research, or relevant work experience) • 4+ years of related industry experience in the data science domain • Expertise in Python or Java with the ability to write performant production-quality code • Familiarity with SQL • Knowledge of Spark and cloud data environments (e.g. AWS, Databricks) • Experience building and scaling machine learning models in business applications using large amounts of data • Ability to communicate and explain data science concepts to diverse audiences • Focus on business practicality and the 80/20 rule • Agile development mindset • It's great, but not required, if you have experience working in a consumer or B2C space for a SaaS product provider • Experience in developing deep learning-based models and working on LLM-related applications • Excelling in solving ambiguous and complex problems

🏖️ Benefits

• Health coverage • Paid volunteer days • Wellness resources