OPT ML Engineer Jobs
ML Engineer jobs are among the most OPT-friendly roles in tech. Most positions require a master's or PhD in computer science, machine learning, or a related field, which aligns well with STEM OPT extension eligibility and gives you up to 36 months of authorized work experience to secure H-1B visa sponsorship.
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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 568+ OPT ML Engineer Jobs
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Get Access To All JobsTips for Finding OPT Sponsorship as a ML Engineer
Target STEM-designated programs from the start
Confirm your degree program carries a STEM designation before applying. ML Engineer roles almost universally qualify for the 24-month STEM OPT extension, giving you three years total to build experience and secure H-1B visa sponsorship.
Prioritize companies with an active H-1B filing history
Search USCIS and DOL disclosure data for employers who have sponsored ML Engineers before. A company with zero prior H-1B filings in technical roles is a real risk when your OPT clock is running.
Raise sponsorship in the offer negotiation stage, not earlier
Wait until you have an offer in hand before discussing H-1B sponsorship. Raising it during screening signals uncertainty and can eliminate you early, especially when competing against candidates who don't need authorization.
Frame your ML research as direct production value
Recruiters at sponsoring companies care about deployment, not just experimentation. Connect your thesis work, research projects, or academic publications to real-world applications like recommendation systems, NLP pipelines, or computer vision at scale.
Apply to Series B and later startups, not just large tech firms
Growth-stage companies often sponsor ML Engineers because the talent pool is thin and the visa cost is a small fraction of the role's value. Many OPT students overlook this tier and limit themselves to big tech.
File your STEM OPT extension well before your initial OPT expires
USCIS recommends filing at least 90 days before expiration. A timely filing preserves your work authorization automatically during processing. Missing the window creates gaps that can disqualify you from roles mid-interview process.
ML Engineer OPT: Frequently Asked Questions
Can I work as an ML Engineer on OPT without H-1B sponsorship?
Yes. OPT authorizes full-time employment in a role directly related to your degree, so you can work as an ML Engineer immediately after graduation. The H-1B becomes relevant once your OPT period ends. If your degree is STEM-designated, you have up to 36 months total before needing a different visa status.
Do ML Engineer roles typically qualify for the STEM OPT extension?
Almost all ML Engineer positions qualify, because the role requires applied knowledge from a STEM field and the work is directly tied to that degree. The key requirement is that your academic program holds a STEM designation, not the job title itself. Degrees in computer science, electrical engineering, statistics, and data science all commonly qualify.
Where can I find ML Engineer jobs that are open to OPT students?
Migrate Mate is built specifically for F-1 OPT and visa-sponsored candidates. You can browse ML Engineer listings filtered by sponsorship willingness, which saves significant time compared to applying broadly and discovering late in the process that a company won't sponsor. It's the most direct way to focus your search on employers who are already open to hiring international talent.
Does my ML Engineer role need to match my degree field exactly to count toward OPT?
It needs to be directly related to your degree, but an exact title match isn't required. A computer science graduate working as an ML Engineer satisfies the requirement clearly. If your degree is in a neighboring field like applied mathematics or statistics, you'll want to document how the role draws on that academic background in case your DSO or USCIS asks.
What happens to my OPT if my ML Engineer job ends before I find a new one?
You have a cumulative 90-day unemployment allowance during your OPT period, and an additional 60 days during the STEM extension, for a total of 150 days. These periods don't reset between jobs. You must report any employment gap to your DSO promptly, and your next role still needs to be directly related to your degree field.