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.
Find OPT Machine Learning JobsOverview
Showing 5 of 750+ Machine Learning jobs
See all 750+ Machine Learning Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Machine Learning roles.
Get Access To All JobsDESCRIPTION
Do you want to join an innovative team of scientists who develop Agentic AI, LLM, and deep learning based solutions to help Amazon provide the best seller experience across the entire Seller life cycle, including recruitment, growth, support, risk mitigation and provide the best customer and seller experience?
Do you want to build advanced algorithmic systems that help manage the trust and safety of millions of customer interactions every day? Are you excited by the prospect of analyzing and modeling terabytes of data and creating state-of-the-art algorithms to solve real world problems? Are you excited by the opportunity to leverage GenAI and innovate on top of the state-of-the-art large language models to improve customer and seller experience?
Do you like to build end-to-end business solutions and directly impact the profitability of the company? Do you like to innovate and create solutions that have cross-organizational impacts?
If yes, then you may be a great fit to join the Machine Learning Accelerator team.
Key job responsibilities
The scope of an Applied Scientist in the Machine Learning Accelerator (MLA) team is to research and prototype AI and Machine Learning applications that solve strategic business problems across Selling Partner Experience (SPX) domains. Additionally, the scientist collaborates with engineers and business partners to design and implement solutions at scale that are of broad benefit to SPX organizations. They develop large-scale solutions for high impact projects, introduce tools and other techniques that can be used to solve problems from various perspectives, and show depth and competence in more than one area. They influence the team’s technical strategy by making insightful contributions to the team’s priorities, approach and planning. They develop and introduce tools and practices that streamline the work of the team, and they mentor junior team members and participate in hiring.
BASIC QUALIFICATIONS
- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- 3+ years of building machine learning models or developing algorithms for business application experience
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- Experience programming in Java, C++, Python or related language
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
- Experience with Machine Learning and Large Language Model fundamentals, including architecture, training/inference lifecycles, and optimization of model execution, or experience in developing and deploying LLMs in production on GPUs, Neuron, TPU or other AI acceleration hardware
PREFERRED QUALIFICATIONS
- Experience using Unix/Linux
- Experience in state-of-the-art deep learning models architecture design and deep learning training and optimization and model pruning
- Experience with LLM fine-tuning, in-context learning, or model evaluation
- Hands-on experience designing reward models or RL post-training pipelines (PPO/GRPO, DPO) for LLMs or agents, including preference-data collection and evaluation
- Experience building agentic AI systems — tool use, planning, retrieval-augmented generation, or multi-agent workflows
- Experience with researching and developing neuro-symbolic solutions and applications
- Publications at top ML/AI venues
- Experience partnering with product/engineering teams to deliver ML in large-scale production system
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
LOCATION
USA, CA, San Diego
COMPENSATION
- Salary Range: $142,800.00 - $193,200.00 USD annually
DESCRIPTION
Do you want to join an innovative team of scientists who develop Agentic AI, LLM, and deep learning based solutions to help Amazon provide the best seller experience across the entire Seller life cycle, including recruitment, growth, support, risk mitigation and provide the best customer and seller experience?
Do you want to build advanced algorithmic systems that help manage the trust and safety of millions of customer interactions every day? Are you excited by the prospect of analyzing and modeling terabytes of data and creating state-of-the-art algorithms to solve real world problems? Are you excited by the opportunity to leverage GenAI and innovate on top of the state-of-the-art large language models to improve customer and seller experience?
Do you like to build end-to-end business solutions and directly impact the profitability of the company? Do you like to innovate and create solutions that have cross-organizational impacts?
If yes, then you may be a great fit to join the Machine Learning Accelerator team.
Key job responsibilities
The scope of an Applied Scientist in the Machine Learning Accelerator (MLA) team is to research and prototype AI and Machine Learning applications that solve strategic business problems across Selling Partner Experience (SPX) domains. Additionally, the scientist collaborates with engineers and business partners to design and implement solutions at scale that are of broad benefit to SPX organizations. They develop large-scale solutions for high impact projects, introduce tools and other techniques that can be used to solve problems from various perspectives, and show depth and competence in more than one area. They influence the team’s technical strategy by making insightful contributions to the team’s priorities, approach and planning. They develop and introduce tools and practices that streamline the work of the team, and they mentor junior team members and participate in hiring.
BASIC QUALIFICATIONS
- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- 3+ years of building machine learning models or developing algorithms for business application experience
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- Experience programming in Java, C++, Python or related language
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
- Experience with Machine Learning and Large Language Model fundamentals, including architecture, training/inference lifecycles, and optimization of model execution, or experience in developing and deploying LLMs in production on GPUs, Neuron, TPU or other AI acceleration hardware
PREFERRED QUALIFICATIONS
- Experience using Unix/Linux
- Experience in state-of-the-art deep learning models architecture design and deep learning training and optimization and model pruning
- Experience with LLM fine-tuning, in-context learning, or model evaluation
- Hands-on experience designing reward models or RL post-training pipelines (PPO/GRPO, DPO) for LLMs or agents, including preference-data collection and evaluation
- Experience building agentic AI systems — tool use, planning, retrieval-augmented generation, or multi-agent workflows
- Experience with researching and developing neuro-symbolic solutions and applications
- Publications at top ML/AI venues
- Experience partnering with product/engineering teams to deliver ML in large-scale production system
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
LOCATION
USA, CA, San Diego
COMPENSATION
- Salary Range: $142,800.00 - $193,200.00 USD annually
See all 750+ 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.