STEM OPT Sr Staff Machine Learning Engineer Jobs
Sr Staff Machine Learning Engineer roles sit squarely within STEM OPT eligibility, drawing on degrees in computer science, statistics, and related STEM fields. Your 24-month extension requires an E-Verify enrolled employer and a signed I-983 training plan tied directly to your ML engineering work.
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INTRODUCTION
At Palo Alto Networks®, we’re united by a shared mission—to protect our digital way of life. We thrive at the intersection of innovation and impact, solving real-world problems with cutting-edge technology and bold thinking. Here, everyone has a voice, and every idea counts. If you’re ready to do the most meaningful work of your career alongside people who are just as passionate as you are, you’re in the right place.
Who We Are
In order to be the cybersecurity partner of choice, we must trailblaze the path and shape the future of our industry. This is something our employees work at each day and is defined by our values: Disruption, Collaboration, Execution, Integrity, and Inclusion. We weave AI into the fabric of everything we do and use it to augment the impact every individual can have. If you are passionate about solving real-world problems and ideating beside the best and the brightest, we invite you to join us!
We believe collaboration thrives in person. That’s why most of our teams work from the office full time, with flexibility when it’s needed. This model supports real-time problem-solving, stronger relationships, and the kind of precision that drives great outcomes.
JOB SUMMARY
Your Impact
Key Responsibilities
- Design, build, and operate production machine learning systems that balance model quality, cost, latency, and reliability in a security-sensitive environment.
- Own the end-to-end lifecycle of ML and LLM components, from problem formulation and model development to production deployment, monitoring, and iterative improvement.
- Integrate ML and LLM-based services with backend systems and data pipelines, ensuring scalability, observability, and safe operation in production.
- Develop and maintain automated training, evaluation, and retraining pipelines, and build data analysis tools to continuously improve model performance as data and threats evolve.
- Partner closely with Product Managers and domain experts to translate product and security requirements into robust ML solutions with clear success metrics.
- Collaborate with software engineers and SREs on release planning, deployment strategies, monitoring, and incident response to ensure reliable and predictable production behavior.
QUALIFICATIONS
Required Qualifications
- MS or Ph.D. in Computer Science or a related field, with a focus on Machine Learning, and 4+ years of industry experience delivering ML systems in production environments.
- Strong problem solver with collaborative team player with clear communication skills, able to work effectively across engineering, product, and SRE teams.
- Solid foundation in Machine Learning, Deep Learning, and NLP, with hands-on experience using modern architectures such as transformer-based models and representation learning techniques.
- Practical experience applying Large Language Models (LLMs) to real-world problems, including text understanding, classification, extraction, summarization, or reasoning over large-scale and noisy data.
- Experience designing, implementing, and operating LLM-powered components in production, including prompt design, model adaptation or fine-tuning, evaluation, and cost/performance optimization.
- Experience with MLOps / AIOps practices for operating ML and LLM systems in production, including model lifecycle management, monitoring, logging, alerting, retraining workflows, and debugging production issues.
- Understanding of model quality, robustness, and safety considerations, including evaluation methodologies, failure modes, and guardrails required for production ML systems in security-sensitive environments.
- Strong experience with ML frameworks, libraries, and tooling (e.g., PyTorch, Tensorflow, Keras, Scikit-learn, Kubeflow), and solid software engineering fundamentals.
- Ability to independently own ML features end-to-end, from problem formulation and system design to implementation, deployment, and iterative improvement in production.
- Proficient in Python, working knowledge of Java, Linux, and shell scripting.
- Experience building and operating services on cloud platforms (GCP and/or AWS) and in containerized environments (Docker, Kubernetes).
Preferred Qualifications
- Familiarity with AI agent–based approaches, such as multi-step inference pipelines, tool-augmented LLM workflows, or systems that combine models, heuristics, and external signals to drive reliable decisions.
- Experience with website content understanding, website classifications, security, or large-scale internet data is a strong plus.
- Familiarity with relational and NoSQL data stores such as MySQL, MongoDB, or similar systems.
- Experience applying LLMs and agentic systems in security-sensitive or high-precision domains is a strong plus.
COMPENSATION DISCLOSURE
The compensation offered for this position will depend on qualifications, experience, and work location. For candidates who receive an offer at the posted level, the starting base salary (for non-sales roles) or base salary + commission target (for sales/commissioned roles) is expected to be the annual range listed below. The offered compensation may also include restricted stock units and a bonus. A description of our employee benefits may be found here.
- $141,000.00 - $228,075.00/yr
OUR COMMITMENT
We’re trailblazers that dream big, take risks, and challenge cybersecurity’s status quo. It’s simple: we can’t accomplish our mission without diverse teams innovating, together.
We are committed to providing reasonable accommodations for all qualified individuals with a disability. If you require assistance or accommodation due to a disability or special need, please contact us at accommodations@paloaltonetworks.com.
Palo Alto Networks is an equal opportunity employer. We celebrate diversity in our workplace, and all qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or other legally protected characteristics.
All your information will be kept confidential according to EEO guidelines.
Is role eligible for Immigration Sponsorship?: Yes
LOCATION
Santa Clara, California, United States
Tips for Finding STEM OPT Authorization as a Sr Staff Machine Learning Engineer
Verify your CIP code before applying
Pull your degree's Classification of Instructional Programs code from your transcripts and confirm it maps to an approved STEM field on the official STEM Designated Degree Program List. Computer science, applied mathematics, and statistics are all qualifying fields for Sr Staff ML Engineer roles.
Check E-Verify enrollment before every interview
Any company that hires you for STEM OPT must be actively enrolled in E-Verify, not just registered. Confirm enrollment status directly through the E-Verify employer search before you invest time in their interview process.
Build a training plan around ML engineering deliverables
Your I-983 must tie every training goal to actual job duties, so draft it before your start date with specifics: model deployment pipelines, distributed training infrastructure, or MLOps tooling. Vague plans draw DSO scrutiny and slow your extension approval.
Target companies with senior IC engineering tracks
Sr Staff roles sit above Staff but below Principal or Distinguished Engineer, so prioritize employers whose job ladders include that tier explicitly. Companies with mature ML infrastructure, such as those running large-scale model serving or autonomous systems, are most likely to post at this seniority.
Use Migrate Mate to filter for E-Verify employers hiring at this level
Search Sr Staff Machine Learning Engineer listings on Migrate Mate, which surfaces only employers verified to support STEM OPT. Filtering by seniority and E-Verify status upfront cuts the time you waste pursuing roles that can't legally employ you.
Negotiate your offer timeline around your OPT end date
If your initial 12-month OPT expires before your extension is approved, the cap-gap rule protects H-1B registrants, but STEM OPT extensions don't work the same way. File your I-765 extension at least 90 days before your EAD expires and confirm the offer start date aligns with your authorized period.
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Find Sr Staff Machine Learning Engineer JobsFrequently Asked Questions
Does my degree qualify me for a STEM OPT extension in a Sr Staff Machine Learning Engineer role?
Your degree qualifies if it carries a STEM-designated CIP code, which covers computer science, electrical engineering, applied mathematics, statistics, and several adjacent fields. The role itself must also relate directly to your degree field. Confirm your CIP code appears on the official STEM Designated Degree Program List maintained by the Department of Homeland Security, and verify the connection with your DSO before applying.
Does the employer offering me a Sr Staff Machine Learning Engineer position need to be E-Verify enrolled?
Yes, E-Verify enrollment is a hard requirement for STEM OPT, not optional. Before accepting any offer, use the E-Verify employer search to confirm the specific legal entity, not just the parent company, is actively enrolled. A subsidiary or staffing agency operating under a different EIN may not share the parent's enrollment, which would invalidate your STEM OPT authorization.
What goes into the I-983 training plan for a Sr Staff ML Engineer role?
The I-983 must describe how your training goals connect to your STEM degree and to the specific technical work you'll perform. For a Sr Staff Machine Learning Engineer, that means listing concrete deliverables: designing model training pipelines, architecting inference systems, or leading research-to-production workflows. Generic descriptions like 'machine learning work' are insufficient. Your employer's authorized representative and your DSO must both sign the plan before your extension is filed.
How do I find Sr Staff Machine Learning Engineer jobs where employers already understand STEM OPT requirements?
Migrate Mate lists Sr Staff Machine Learning Engineer openings filtered to E-Verify enrolled employers, so you're only seeing roles where the legal groundwork is already in place. At the Sr Staff level, hiring managers in ML-intensive organizations tend to be more familiar with STEM OPT than early-career teams, but confirming E-Verify status yourself before the offer stage remains essential regardless of employer size.
What happens to my STEM OPT authorization if my extension is still pending when my current EAD expires?
If you filed a timely STEM OPT extension, meaning at least 90 days before your EAD expiration, USCIS grants a 180-day automatic extension of your work authorization while the application is pending. You can continue working for your E-Verify employer during that window. Your employer must re-verify your employment authorization in E-Verify once your new EAD arrives.
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