OPT Machine Learning Manager Jobs
Machine Learning Manager jobs on OPT require employers who can sponsor H-1B visa or support STEM OPT extensions, since the role typically falls under Computer and Information Research as a specialty occupation. Most positions demand 5-plus years of ML experience, making early OPT the right time to target senior IC roles that lead to management tracks.
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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 Manager Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new OPT Machine Learning Manager Jobs.
Get Access To All JobsTips for Finding OPT Sponsorship as a Machine Learning Manager
Confirm the role qualifies as a specialty occupation
Machine Learning Manager positions almost always require a bachelor's degree or higher in computer science, statistics, or a related field. Verify the job posting explicitly states a degree requirement, not just a preference, to ensure your OPT authorization aligns cleanly.
Target employers with an established H-1B track record
Companies that have sponsored ML engineers and data scientists before are far more likely to sponsor a Machine Learning Manager. Search employer H-1B visa disclosure data through the Department of Labor to confirm a pattern of sponsorship before investing time in applications.
Clarify your OPT timeline upfront with recruiters
Machine Learning Manager hiring cycles run long, often 8 to 12 weeks. If your OPT expiration is within six months, raise your timeline early so employers can assess whether they can complete H-1B sponsorship before your authorization lapses.
Lead with your STEM OPT extension eligibility
A STEM OPT extension gives you up to three additional years of work authorization, which meaningfully reduces urgency for employers. If your degree is in computer science, data science, or a related STEM field, mention this extension explicitly in your cover letter and recruiter conversations.
Demonstrate cross-functional leadership to differentiate yourself
Machine Learning Manager roles require leading engineers, aligning with product teams, and owning model deployment decisions. Candidates who can show tangible team leadership experience, not just technical depth, stand out and reduce employer hesitation around sponsorship investment.
Focus on companies scaling ML infrastructure, not just experimenting
Organizations at the proof-of-concept stage rarely commit to sponsorship for senior hires. Target employers actively productionizing ML systems, with dedicated ML platform teams, as they have stronger business reasons to sponsor and retain a capable manager long term.
Machine Learning Manager OPT: Frequently Asked Questions
Can I work as a Machine Learning Manager on OPT?
Yes, provided your role qualifies as a specialty occupation requiring a degree in a directly related field like computer science, electrical engineering, or applied mathematics. Machine Learning Manager positions consistently meet this standard. Your OPT authorization must remain valid, and the job must be directly related to your degree field.
Do Machine Learning Manager jobs commonly offer H-1B sponsorship?
Many do, particularly at mid-size and large technology companies that depend on ML infrastructure for their core products. Firms in sectors like cloud computing, fintech, and health tech regularly sponsor ML leadership roles. Migrate Mate filters sponsorship-friendly employers so you can focus your search on companies with a documented history of supporting international candidates.
Does my degree field affect OPT eligibility for this role?
Yes. Your OPT work must be directly related to your degree. A Machine Learning Manager role is most straightforwardly supported by degrees in computer science, data science, statistics, or electrical engineering. If your degree is adjacent, such as applied mathematics or operations research, you can still qualify, but you may need to clearly articulate the connection on your OPT reporting documentation.
How does STEM OPT extension work for Machine Learning Manager roles?
If your bachelor's, master's, or doctoral degree is in a STEM-designated field, you can apply for a 24-month STEM OPT extension after your initial 12-month OPT period. The employer must be E-Verify enrolled and agree to a formal training plan. For Machine Learning Manager roles, most qualifying employers are already E-Verify participants, making the extension straightforward to execute.
What should I do if my OPT expires before an employer completes H-1B sponsorship?
The timing risk is real for management-level roles, where hiring decisions move slowly. If an approved H-1B petition is in place before your OPT expires, you can maintain status through the cap-gap provision while waiting for October 1 employment to begin. Working closely with an immigration attorney and starting conversations with employers at least six months before expiration significantly reduces the risk of a gap.