Pay
Higher than most similar jobs
$276K against $166K–$240K, the middle half of what similar US postings state.
From 1,279 postings in the last year. Stated ranges, not salaries paid.
Senior Machine Learning Engineer
San Francisco, CA
Actively hiring, first seen by us 7 days ago- Pay
$276,200/year — pay source
Design, develop, and train cutting-edge world class machine learning models (including NER, personalization, prediction, and LLM fine-tuning) to power Atlassian products. Ship production-ready ML systems by collaborating with engineering, product, and analytics teams to integrate AI features into Atlassian services as well as performing machine learning model optimization techniques and writing production quality code. Conduct experimentation and model evaluation, ensuring performance, scalability, and reliability of deployed models. Define and monitor product metrics, using data analysis to guide improvements and measure impact. Contribute to Atlassian's next-gen AI initiatives, including foundational model development and researching and advancing the state of ML techniques to land new unique features for Atlassian's AI offerings. Communicate findings and recommendations to senior leaders through clear presentations and insights. 40 hrs/week, Mon-Fri, 8:30 a.m. - 5:30 p.m. Salary: $276,200/yr. Compensation
Read the full posting- Work setting
- Not stated
- Employment
- Not stated
What you’ll work on
Full postingDesign, develop and train ML models such as NER, personalization and LLM fine-tuning
Ship production-ready ML systems and integrate AI features into Atlassian services
Run experiments and model evaluations, ensuring deployed models are performant and reliable
Define and monitor product metrics using data analysis
Present findings and recommendations to senior leaders
From the employer’s posting
Design, develop, and train cutting-edge world class machine learning models (including NER, personalization, prediction, and LLM fine-tuning) to power Atlassian products.
Ship production-ready ML systems by collaborating with engineering, product, and analytics teams to integrate AI features into Atlassian services
Conduct experimentation and model evaluation, ensuring performance, scalability, and reliability of deployed models.
Define and monitor product metrics, using data analysis to guide improvements and measure impact.
Communicate findings and recommendations to senior leaders through clear presentations and insights.
What you’ll bring
All qualificationsCore experience
- 100% Telecommuting is permitted.
Qualification wording
100% Telecommuting is permitted.
Education & alternatives
Qualifications MINIMUM REQUIREMENTS:Master's degree or foreign equivalent degree in Computer Science, Electrical Engineering, or a related field of study, and three (3) years of related work experience. Must have three (3) years of experience with/in:
Benefits in the posting
Full benefits wording- Atlassian offers a wide range of perks and benefits designed to support you, your family and to help you engage with your local community. Our offerings include health and wellbeing resources, paid volunteer days, and so much more. To learn more, visit go.atlassian.com/perksandbenefits.
From the employer’s posting.
About Atlassian
At Atlassian, we're motivated by a common goal: to unleash the potential of every team.
In the employer’s words · Read in context
Posting record
Report an errorActively hiringFirst seen by us 7 days ago, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Oct 27, 20267 days ago
- Recorded sightings
- 10
- Last seen by us
- Nov 2, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Time since we first saw it
Day 7
Similar jobs usually come down between day 6 and day 69.
From 4,284 similar postings that came down. Coming down is not always a hire.
Atlassian is hiring
49 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- ML Engineer hiring is steady
- Takes jobs down at a usual pace
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Java
- Python
- SQL
- AWS
- Azure
- Databricks
- Excel
- Looker
- Power BI
- Spark
- Tableau
Where the posting names them
- Building and scaling machine learning models using large amounts of data - Utilizing Python or Java to write performant production-quality code - Anomaly detection for dataset analysis for the purpose of training, validating, and shipping machine learning models
- Agile development practices - SQL - BI tooling using Tableau, Excel, Power BI, or Looker
Must have three (3) years of experience with/in: - Spark and Cloud data environments (AWS, Databricks, or Azure) - Building and scaling machine learning models using large amounts of data
- SQL - BI tooling using Tableau, Excel, Power BI, or Looker 100% Telecommuting is permitted.
Your next step
Complete your application on careers-americas.icims.com. The employer’s form will show what is required.
Applying through iCIMS
- You start with your email. New applicants then create a login, and returning ones sign in.
- Upload your resume before you fill anything in: iCIMS fills some profile fields from it.
- Check your status on the employer’s iCIMS Dashboard, under Past Job Submittals.
Already applied? Track this application
Has Atlassian posted this job before?
Yes. We’ve followed 10 other Senior Machine Learning Engineer jobs there since September 2026. All 10 are still up.
Large employers often post one title for several teams, so these can be separate openings.
About the role
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
US government figures for computer and information research scientists
- Median yearly pay, May 2025
- $140,300
- Expected change, 2025 to 2035
- 21.8% more jobsagainst 3.5% for all jobs
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
Job description
Overview
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
Design, develop, and train cutting-edge world class machine learning models (including NER, personalization, prediction, and LLM fine-tuning) to power Atlassian products. Ship production-ready ML systems by collaborating with engineering, product, and analytics teams to integrate AI features into Atlassian services as well as performing machine learning model optimization techniques and writing production quality code. Conduct experimentation and model evaluation, ensuring performance, scalability, and reliability of deployed models. Define and monitor product metrics, using data analysis to guide improvements and measure impact. Contribute to Atlassian's next-gen AI initiatives, including foundational model development and researching and advancing the state of ML techniques to land new unique features for Atlassian's AI offerings. Communicate findings and recommendations to senior leaders through clear presentations and insights.
40 hrs/week, Mon-Fri, 8:30 a.m. - 5:30 p.m. Salary: $276,200/yr.
Compensation
At Atlassian, we strive to design equitable, explainable, and competitive compensation programs. We follow consistent hiring practices and account for each candidate's skills, knowledge, and experience when setting base pay within the range.
Please visit go.atlassian.com/payzones for more information on which locations are included in each of our geographic pay zones. However, please confirm the zone for your specific location with your recruiter.
This role may also be eligible for benefits, bonuses, commissions, and equity.
Qualifications
MINIMUM REQUIREMENTS:Master's degree or foreign equivalent degree in Computer Science, Electrical Engineering, or a related field of study, and three (3) years of related work experience.
Must have three (3) years of experience with/in:
Spark and Cloud data environments (AWS, Databricks, or Azure)
Building and scaling machine learning models using large amounts of data
Utilizing Python or Java to write performant production-quality code
Anomaly detection for dataset analysis for the purpose of training, validating, and shipping machine learning models
Agile development practices
SQL
BI tooling using Tableau, Excel, Power BI, or Looker
100% Telecommuting is permitted.
Please email resume to: postings@atlassian.com and must reference Job code: "CA013" to be considered
Benefits & Perks
Atlassian offers a wide range of perks and benefits designed to support you, your family and to help you engage with your local community. Our offerings include health and wellbeing resources, paid volunteer days, and so much more. To learn more, visit go.atlassian.com/perksandbenefits.
About Atlassian
At Atlassian, we're motivated by a common goal: to unleash the potential of every team. Our software products help teams all over the planet and our solutions are designed for all types of work. Team collaboration through our tools makes what may be impossible alone, possible together.
We believe that the unique contributions of all Atlassians create our success. To ensure that our products and culture continue to incorporate everyone's perspectives and experience, we never discriminate based on race, religion, national origin, gender identity or expression, sexual orientation, age, or marital, veteran, or disability status. All your information will be kept confidential according to EEO guidelines.
To provide you the best experience, we can support with accommodations or adjustments at any stage of the recruitment process. Simply inform our Recruitment team during your conversation with them.
To learn more about our culture and hiring process, visit go.atlassian.com/crh.
In line with local law, identity verification (which may include use of biometric data) is a condition of employment with Atlassian for employment fraud purposes.
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
Design, develop, and train cutting-edge world class machine learning models (including NER, personalization, prediction, and LLM fine-tuning) to power Atlassian products. Ship production-ready ML systems by collaborating with engineering, product, and analytics teams to integrate AI features into Atlassian services as well as performing machine learning model optimization techniques and writing production quality code. Conduct experimentation and model evaluation, ensuring performance, scalability, and reliability of deployed models. Define and monitor product metrics, using data analysis to guide improvements and measure impact. Contribute to Atlassian's next-gen AI initiatives, including foundational model development and researching and advancing the state of ML techniques to land new unique features for Atlassian's AI offerings. Communicate findings and recommendations to senior leaders through clear presentations and insights. 40 hrs/week, Mon-Fri, 8:30 a.m. - 5:30 p.m. Salary: $276,200/yr. Compensation
- Location & working pattern
San Francisco, CA
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.