OPT Machine Learning Engineer Jobs
Machine Learning Engineer roles are among the most OPT-friendly positions in tech, with high demand from employers already familiar with F-1 work authorization. Most roles qualify as STEM OPT, giving you up to 36 months of work authorization, and many employers actively file H-1B visa petitions for strong ML candidates.
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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 Engineer Jobs
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Get Access To All JobsTips for Finding OPT Sponsorship as a Machine Learning Engineer
Target companies with active H-1B filing histories
Large tech firms and well-funded AI startups file H-1B visa petitions regularly for ML roles. Filtering by employers with consistent sponsorship track records is the most reliable way to avoid wasting applications on companies that won't convert your OPT.
Lead with your research output and production deployments
Employers sponsoring ML engineers want evidence of real impact. Published papers, Kaggle rankings, open-source contributions, and deployed models in production all signal the kind of technical depth that makes sponsorship worth the investment for a hiring manager.
Apply before your OPT start date, not after
Most ML hiring pipelines take six to twelve weeks from application to offer. Starting your search three to four months before your OPT authorization date gives employers enough runway to complete interviews and onboarding before your work authorization begins.
Clarify your STEM OPT extension eligibility upfront
ML Engineering consistently qualifies under STEM OPT CIP codes tied to computer science and data science programs. Confirming your degree program qualifies before interviews prevents late-stage confusion and reassures employers that 36 months of authorization is on the table.
Specialize in a high-demand ML subfield
Employers sponsoring visas need strong justification for the cost. Specializing in LLM fine-tuning, computer vision, or MLOps makes you a clearer candidate for roles that are genuinely hard to fill, which strengthens the business case for sponsorship.
Negotiate H-1B filing into your offer conversation early
Bringing up sponsorship after receiving an offer creates friction. Raising it naturally during late-stage interviews, once the employer is clearly interested, lets you confirm their willingness to file before you invest further time in the process.
Machine Learning Engineer OPT: Frequently Asked Questions
Do Machine Learning Engineer jobs typically qualify for STEM OPT extension?
Yes. Machine Learning Engineering falls under CIP codes tied to computer science, data science, and electrical engineering programs, all of which are on the STEM Designated Degree Program list. If your degree is in one of those fields, you're eligible to apply for the 24-month STEM OPT extension, giving you up to 36 months of total work authorization.
How do I find Machine Learning Engineer jobs where the employer is willing to sponsor OPT and H-1B?
Migrate Mate filters jobs specifically for F-1 OPT students, so the roles listed are from employers familiar with or actively open to sponsorship. Browsing ML Engineer listings on Migrate Mate saves significant time compared to filtering through general job boards where most postings don't address visa sponsorship at all.
Can I work as a Machine Learning Engineer on OPT before my STEM extension is approved?
Yes, as long as your initial 12-month OPT authorization is active and you've submitted your STEM OPT extension application before it expires. USCIS automatically extends your work authorization by up to 180 days while the extension is pending, so there's no gap in your ability to work, provided you filed on time.
What employment relationship counts as valid for STEM OPT in an ML role?
STEM OPT requires a formal employer-employee relationship, meaning your employer must provide supervision, control your work schedule, and report training outcomes through the SEVP portal. Fully independent contracting arrangements do not satisfy this requirement. Most full-time ML Engineering positions at tech companies meet the standard, but contract-to-hire roles should be reviewed with your DSO before accepting.
Do employers need to pay OPT students market rate for Machine Learning Engineer roles?
STEM OPT regulations require that employers pay OPT students the same wages and working conditions offered to similarly situated U.S. workers in the same role and location. For ML Engineering, which commands strong compensation across the industry, this protection matters. If an employer offers terms noticeably below what comparable full-time employees receive, that arrangement likely doesn't comply with STEM OPT requirements.