OPT Machine Learning Jobs
Machine learning roles are among the most OPT-friendly in tech. Most positions require a master's or PhD in computer science, statistics, or a related field, and STEM OPT extensions apply, giving you up to three years of authorized work. Employers in this space file H-1B visa petitions at high rates, making ML a strong long-term visa path.
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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.
Interviews and onboarding are conducted virtually, a part of being a distributed-first company.
Atlassian is seeking a Senior Machine Learning Engineer to join our Central AI team.
The Central AI organization constructs the fundamental infrastructure, data pipeline, frameworks, models, and other capabilities to expedite AI feature development throughout the entire company.
YOUR FUTURE TEAM
The Central AI org is part of the larger Atlassian Intelligence program. Its purpose is to accelerate AI innovation across all our products and platform, provide cohesive AI experiences and set up an Atlassian AI infrastructure for the future. Additionally, Central AI is responsible for developing some of the core shared experiences typical in the AI domain, such as search, knowledge discovery, and conversation.
Responsibilities:
What you’ll do
As a Senior Machine Learning engineer, you will work on the development and implementation of the cutting-edge machine learning algorithms, training sophisticated models, collaborating with product, engineering, and analytics teams, to build the AI functionalities into each Atlassian product and service.
Your daily responsibilities will encompass a broad spectrum of tasks such as designing system and model architectures, conducting rigorous experimentation and model evaluations, and providing guidance to junior ML engineers. Your role is pivotal, stretching beyond these tasks, ensuring AI's transformative potential is realized across our offerings.
PAY RANGES:
In The United States, we have three geographic pay zones. For this role, our current base pay ranges for new hires in each zone are:
Zone A: $206,100 - $269,075
Zone B: $185,490 - $242,168
Zone C: $171,063 - $223,332
QUALIFICATIONS
On the first day, we'll expect you to have
Bachelor's or Master's degree (preferably a Computer Science degree or equivalent experience)
3+ 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
Agile development mindset, appreciating the benefit of constant iteration and improvement
It's great, but not required, if you have
Experience working in a consumer or B2C space for a SaaS product provider, or the enterprise/B2B space
Experience in developing deep learning-based models and working on LLM-related applications
Excelling in solving ambiguous and complex problems, being able to navigate through uncertain situations, breaking down complex challenges into manageable components and developing innovative solutions
COMPENSATION
At Atlassian, we strive to design equitable, explainable, and competitive compensation programs. To support this goal, the baseline of our range is higher than that of the typical market range, but in turn, we expect to hire most candidates near this baseline. Base pay within the range is ultimately determined by a candidate's skills, expertise, or experience.
In the United States, we have three geographic pay zones. For this role, our current base pay ranges for new hires in each zone are:
Zone A: $206,100 - $269,075
Zone B: $185,490 - $242,168
Zone C: $171,063 - $223,332
This role may also be eligible for benefits, bonuses, commissions, and equity.
Please visit go.atlassian.com/payzones for more information on which locations are included in each of our geographic pay zones.
Please visit go.atlassian.com/perksandbenefits to learn more about our perks and benefits.
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.
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.
Interviews and onboarding are conducted virtually, a part of being a distributed-first company.
Atlassian is seeking a Senior Machine Learning Engineer to join our Central AI team.
The Central AI organization constructs the fundamental infrastructure, data pipeline, frameworks, models, and other capabilities to expedite AI feature development throughout the entire company.
YOUR FUTURE TEAM
The Central AI org is part of the larger Atlassian Intelligence program. Its purpose is to accelerate AI innovation across all our products and platform, provide cohesive AI experiences and set up an Atlassian AI infrastructure for the future. Additionally, Central AI is responsible for developing some of the core shared experiences typical in the AI domain, such as search, knowledge discovery, and conversation.
Responsibilities:
What you’ll do
As a Senior Machine Learning engineer, you will work on the development and implementation of the cutting-edge machine learning algorithms, training sophisticated models, collaborating with product, engineering, and analytics teams, to build the AI functionalities into each Atlassian product and service.
Your daily responsibilities will encompass a broad spectrum of tasks such as designing system and model architectures, conducting rigorous experimentation and model evaluations, and providing guidance to junior ML engineers. Your role is pivotal, stretching beyond these tasks, ensuring AI's transformative potential is realized across our offerings.
PAY RANGES:
In The United States, we have three geographic pay zones. For this role, our current base pay ranges for new hires in each zone are:
Zone A: $206,100 - $269,075
Zone B: $185,490 - $242,168
Zone C: $171,063 - $223,332
QUALIFICATIONS
On the first day, we'll expect you to have
Bachelor's or Master's degree (preferably a Computer Science degree or equivalent experience)
3+ 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
Agile development mindset, appreciating the benefit of constant iteration and improvement
It's great, but not required, if you have
Experience working in a consumer or B2C space for a SaaS product provider, or the enterprise/B2B space
Experience in developing deep learning-based models and working on LLM-related applications
Excelling in solving ambiguous and complex problems, being able to navigate through uncertain situations, breaking down complex challenges into manageable components and developing innovative solutions
COMPENSATION
At Atlassian, we strive to design equitable, explainable, and competitive compensation programs. To support this goal, the baseline of our range is higher than that of the typical market range, but in turn, we expect to hire most candidates near this baseline. Base pay within the range is ultimately determined by a candidate's skills, expertise, or experience.
In the United States, we have three geographic pay zones. For this role, our current base pay ranges for new hires in each zone are:
Zone A: $206,100 - $269,075
Zone B: $185,490 - $242,168
Zone C: $171,063 - $223,332
This role may also be eligible for benefits, bonuses, commissions, and equity.
Please visit go.atlassian.com/payzones for more information on which locations are included in each of our geographic pay zones.
Please visit go.atlassian.com/perksandbenefits to learn more about our perks and benefits.
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.
See all 569+ OPT Machine Learning Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new OPT Machine Learning Jobs.
Get Access To All JobsTips for Finding OPT Sponsorship in Machine Learning
Target companies with active H-1B filing histories
Companies that consistently file H-1B visa petitions for ML roles are your best bet for long-term sponsorship. Check OFLC disclosure data for employers with recent machine learning or data science LCA filings to confirm they have an established sponsorship process.
Lead with your STEM OPT timeline
Most ML employers plan hiring on multi-year horizons. Telling recruiters you have up to three years of STEM OPT remaining signals you're not a short-term hire. Frame it as runway, not a constraint, when discussing your work authorization.
Specialize before you apply
Generalist ML resumes get lost. Employers hiring for NLP, computer vision, reinforcement learning, or MLOps want demonstrated depth. Pick a specialization aligned with your coursework or research and build your portfolio and resume around that specific area.
Quantify your model impact in every bullet
ML hiring managers screen for results, not methods. Replace vague descriptions like 'built a classification model' with metrics: accuracy improvements, latency reductions, or business outcomes your model drove. Numbers move resumes past initial filters faster than technical jargon.
Use your research or thesis as a portfolio anchor
If your OPT authorization stems from a graduate program, your thesis or research project is a legitimate work sample. Link to papers, GitHub repositories, or Kaggle notebooks that demonstrate real ML work. Academic output carries weight with technical recruiters.
Apply to mid-size companies, not just large tech firms
Large tech companies attract thousands of OPT applicants for ML roles. Mid-size companies with ML infrastructure needs, such as fintech, healthtech, or autonomous systems firms, often sponsor visas with less competition and faster hiring timelines.
Machine Learning OPT: Frequently Asked Questions
Can I work in machine learning on OPT without employer sponsorship?
Yes, during your OPT period you're authorized to work without your employer filing any petition on your behalf. You just need the role to be directly related to your degree field, which for ML typically means a degree in computer science, statistics, electrical engineering, or a related STEM discipline. Sponsorship only becomes relevant when transitioning to a long-term visa like the H-1B.
Does a machine learning job qualify for the STEM OPT extension?
It does if your degree is on the STEM Designated Degree Program List and the role is directly related to that degree. Most ML positions require quantitative or computer science backgrounds, which are almost universally STEM-designated. Your employer also needs to be enrolled in E-Verify to support the extension, so confirm that before accepting an offer.
Where can I find machine learning jobs that are open to OPT students?
Migrate Mate is built specifically for F-1 OPT students and filters for employers who are open to hiring candidates on work authorization. Searching for machine learning roles on Migrate Mate surfaces positions where sponsorship history or OPT-friendliness has already been factored in, which saves time compared to applying broadly and discovering authorization issues late in the process.
What happens to my OPT if my machine learning role is eliminated or I'm laid off?
You have a 90-day unemployment allowance across your standard OPT period. If you're on the STEM OPT extension, the allowance increases to 150 days total. You must find a new qualifying ML role within that window. The new employer must also be E-Verify enrolled if you're on the extension. Report any employer changes to your DSO promptly to keep your SEVIS record current.
Can I work as a machine learning contractor or freelancer on OPT?
Self-employment on OPT is permitted but requires that the work is directly related to your degree. For ML, that means genuine technical work, not general business activities. You must be able to document the relationship between your degree and the work performed. On STEM OPT, self-employment faces additional restrictions, and your DSO should confirm your specific situation before you structure any freelance arrangement.