OPT AI ML Platform Jobs
AI ML Platform engineering sits at the intersection of infrastructure and machine learning, making it one of the most OPT-friendly specializations in tech. Employers in this space regularly sponsor H-1B visas, and STEM OPT extensions give you up to three years of work authorization to build the track record that makes sponsorship straightforward.
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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 208+ OPT AI ML Platform Jobs
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Get Access To All JobsTips for Finding OPT Sponsorship in AI ML Platform
Target companies with dedicated ML infrastructure teams
Large tech firms and AI-focused startups with dedicated ML platform teams sponsor OPT and H-1B at high rates. Look for engineering organizations where ML infrastructure is a core product function, not a side project maintained by a single engineer.
Lead with platform impact, not just model work
Hiring managers for ML platform roles want engineers who reduce friction for data scientists at scale. Frame your experience around compute cost reduction, training throughput improvements, or pipeline reliability, not just model accuracy benchmarks from academic projects.
Get your STEM OPT extension filed before your OPT expires
Your STEM OPT extension application must be filed at least 90 days before your initial OPT end date. Missing this window means a gap in work authorization. Coordinate early with your DSO and confirm your employer qualifies under E-Verify requirements.
Specialize in a high-demand ML platform layer
Feature stores, model registries, distributed training orchestration, and inference serving are all understaffed relative to demand. Deep expertise in one of these layers makes you a stronger H-1B petition candidate because the specialty occupation requirement is easier to document.
Understand your employer's H-1B sponsorship timeline
H-1B cap-subject petitions can only be filed in April for an October start. If your OPT expires before October, ask whether the employer will file for cap-exempt status or use an academic or nonprofit partner. Clarify this before accepting an offer.
Document your work authorization status clearly in applications
When applying, state your OPT status, your STEM extension eligibility, and your authorization end date upfront. Employers unfamiliar with OPT often assume it means immediate sponsorship costs. Showing you have one to three years of self-authorized work time removes that friction.
AI ML Platform OPT: Frequently Asked Questions
Do AI ML Platform jobs typically qualify for the STEM OPT extension?
Yes. AI ML Platform roles are almost always classified under CIP codes in computer science or electrical engineering, both of which appear on the STEM Designated Degree Program list. As long as your degree is in a qualifying STEM field and your employer participates in E-Verify, you can extend your OPT by 24 months beyond the initial 12, giving you up to three years of work authorization total.
How do I find AI ML Platform jobs that are open to OPT students?
Migrate Mate is built specifically for F-1 OPT students and filters job listings by sponsorship willingness, so you're not wasting time applying to roles where OPT is a disqualifier. AI ML Platform roles are well-represented on the platform because the employers posting there are already accustomed to hiring international talent on OPT and H-1B.
Can I work on an AI ML Platform team at a startup on OPT?
Yes, but verify the startup participates in E-Verify before accepting an offer if you plan to apply for a STEM OPT extension. E-Verify enrollment is a federal requirement for STEM OPT employers, and smaller startups sometimes haven't completed it. Enrollment takes only a few days, so most employers are willing to complete it if they want to hire you.
What makes AI ML Platform a strong field for long-term visa sponsorship?
ML platform engineering is a well-defined specialty occupation with a clear degree requirement in computer science or a related engineering field, which makes H-1B petitions more straightforward to document than generalist software roles. Demand consistently exceeds supply, so employers in this space have strong financial incentives to sponsor rather than lose a qualified candidate to a competitor.
What should I do if my OPT expires before my employer's H-1B petition is approved?
If you filed your H-1B petition before your OPT expired and your status is maintained through cap-gap coverage, you may continue working while the petition is pending. Cap-gap automatically bridges the period between OPT expiration and the October 1 H-1B start date for timely-filed petitions. Confirm with your DSO that your I-20 reflects the cap-gap extension and that your employer's attorney filed before the April deadline.