Machine Learning Engineer Jobs in USA with Visa Sponsorship
Machine learning engineers who build the infrastructure to train, deploy, and monitor ML models at scale are critically needed by US companies operationalizing their data science investments. This role sits at the intersection of software engineering and data science - requiring expertise in feature engineering, model serving, distributed training, and monitoring - which makes it a strong specialty occupation for visa sponsorship. Employers ranging from FAANG to fintech to healthcare AI companies sponsor machine learning engineers because reliable ML infrastructure is what turns experimental models into revenue-generating products. For detailed occupation requirements, see the O*NET profile.
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Get Access To All JobsThe application window is expected to close on: 12/23/2026
This is a hybrid role, requiring 3 days per week on site in San Jose, CA
Meet The Team
Cisco's CX AI Incubation and Agents team owns the foundational AI platform behind intelligent customer experiences across Cisco—the shared layer that application and agent teams across CX build on, in cloud, on-premises, and fully air-gapped customer environments.
Our charter spans the development of AI-native platforms – including model and inference layers, evaluation systems for shipped AI behavior, agentic and orchestration infrastructure, foundational AI services and APIs, and packaging and upgrade capabilities – as well as breakthrough solutions across delivery intelligence, network automation, and edge computing. Our work spans classical ML, domain-specific language models, and Agentic AI.
Your Impact
As a Principal Machine Learning Engineer on Cisco’s CX AI Incubation and Agents team, you tackle ambiguous, high-impact challenges and lead cross-functional engagements from architecture and design through production and customer deployment. You will serve as the architectural and technical authority for designing, building, and scaling the AI foundation powering Cisco IQ and evolving customer needs. As a hands-on technical leader, you will design and build AI systems for production scale. You will set the benchmark for system design, platform governance, and technical excellence across the CX engineering ecosystem.
What You Will Own & Drive
- Foundational AI Platform Architecture: Design and build robust, multi-tenant AI services with scalable APIs, versioning, backward compatibility, and quota management across cloud, on-premises, and air-gapped environments.
- AI Technology Strategy and Execution: Select, evaluate, and implement models, frameworks, inference runtimes, and orchestration technologies. Translate emerging capabilities into production architectures optimized for scalability, latency, memory, and compute across GPU, CPU, and edge environments.
- AI Cost Optimization and Standards: Design and implement cost optimization across workloads by improving token efficiency, model selection, inference performance, and compute utilization. Establish measurable engineering standards for cost efficiency.
- Technical Governance & Leadership by Influence: Lead architecture and design reviews, resolve complex technical trade-offs, mentor senior engineers, and influence platform direction through hands-on technical leadership and execution.
Minimum Qualifications:
- Bachelors + 14 years of related experience, or Masters + 11 years of related experience, or PhD + 7 years of related experience.
- Experience developing, fine-tuning, and optimizing models in Python, PyTorch or JAX, using techniques such as PEFT or LoRA, quantization, and distillation.
- Experience architecting and deploying production LLM and/or SLM inference runtimes optimized with continuous batching, KV-cache management, or speculative decoding.
- Experience architecting and deploying production RAG systems and agentic workflows using vector databases.
- Experience designing and implementing automated evaluation frameworks for AI systems, including golden test datasets, LLM-as-a-judge methodologies, drift detection, and/or CI/CD regression gates.
- Experience architecting production AI platform APIs featuring robust quota management, versioning, and deployment across hybrid cloud and air-gapped environments.
Preferred Qualifications:
- Research & Thought Leadership: Recognized track record of industry contributions via publications, patents, conference presentations, or core contributions to open-source AI/ML projects.
- Edge & Resource-Constrained Inference: Hands-on experience optimizing inference workloads for resource-constrained compute environments (CPU, NPU, small GPU footprints, and on-prem hardware appliances).
Why Cisco?
At Cisco, we’re revolutionizing how data and infrastructure connect and protect organizations in the AI era – and beyond. We’ve been innovating fearlessly for 40 years to create solutions that power how humans and technology work together across the physical and digital worlds. These solutions provide customers with unparalleled security, visibility, and insights across the entire digital footprint.
Fueled by the depth and breadth of our technology, we experiment and create meaningful solutions. Add to that our worldwide network of doers and experts, and you’ll see that the opportunities to grow and build are limitless. We work as a team, collaborating with empathy to make really big things happen on a global scale. Because our solutions are everywhere, our impact is everywhere.
We are Cisco, and our power starts with you.
Message to applicants applying to work in the U.S. and/or Canada:
The starting salary range posted for this position is $296,300.00 to $374,800.00 and reflects the projected salary range for new hires in this position in U.S. and/or Canada locations, not including incentive compensation*, equity, or benefits.
Individual pay is determined by the candidate's hiring location, market conditions, job-related skillset, experience, qualifications, education, certifications, and/or training. The full salary range for certain locations is listed below. For locations not listed below, the recruiter can share more details about compensation for the role in your location during the hiring process.
U.S. employees are offered benefits, subject to Cisco’s plan eligibility rules, which include medical, dental and vision insurance, a 401(k) plan with a Cisco matching contribution, paid parental leave, short and long-term disability coverage, and basic life insurance. Please see the Cisco careers site to discover more benefits and perks. Employees may be eligible to receive grants of Cisco restricted stock units, which vest following continued employment with Cisco for defined periods of time.
U.S. employees are eligible for paid time away as described below, subject to Cisco’s policies:
- 10 paid holidays per full calendar year, plus 1 floating holiday for non-exempt employees
- 1 paid day off for employee’s birthday, paid year-end holiday shutdown, and 4 paid days off for personal wellness determined by Cisco
- Non-exempt employees** receive 16 days of paid vacation time per full calendar year, accrued at rate of 4.92 hours per pay period for full-time employees
- Exempt employees participate in Cisco’s flexible vacation time off program, which has no defined limit on how much vacation time eligible employees may use (subject to availability and some business limitations)
- 80 hours of sick time off provided on hire date and each January 1st thereafter, and up to 80 hours of unused sick time carried forward from one calendar year to the next
- Additional paid time away may be requested to deal with critical or emergency issues for family members
- Optional 10 paid days per full calendar year to volunteer
For non-sales roles, employees are also eligible to earn annual bonuses subject to Cisco’s policies.
Employees on sales plans earn performance-based incentive pay on top of their base salary, which is split between quota and non-quota components, subject to the applicable Cisco plan. For quota-based incentive pay, Cisco typically pays as follows:
- .75% of incentive target for each 1% of revenue attainment up to 50% of quota;
- 1.5% of incentive target for each 1% of attainment between 50% and 75%;
- 1% of incentive target for each 1% of attainment between 75% and 100%; and
- Once performance exceeds 100% attainment, incentive rates are at or above 1% for each 1% of attainment with no cap on incentive compensation.
For non-quota-based sales performance elements such as strategic sales objectives, Cisco may pay 0% up to 125% of target. Cisco sales plans do not have a minimum threshold of performance for sales incentive compensation to be paid.
The applicable full salary ranges for this position, by specific state, are listed below:
New York City Metro Area:
$296,300.00 - $431,000.00
Non-Metro New York state & Washington state:
$263,700.00 - $383,500.00
- For quota-based sales roles on Cisco’s sales plan, the ranges provided in this posting include base pay and sales target incentive compensation combined.
Employees in Illinois, whether exempt or non-exempt, will participate in a unique time off program to meet local requirements.
The application window is expected to close on: 12/23/2026
This is a hybrid role, requiring 3 days per week on site in San Jose, CA
Meet The Team
Cisco's CX AI Incubation and Agents team owns the foundational AI platform behind intelligent customer experiences across Cisco—the shared layer that application and agent teams across CX build on, in cloud, on-premises, and fully air-gapped customer environments.
Our charter spans the development of AI-native platforms – including model and inference layers, evaluation systems for shipped AI behavior, agentic and orchestration infrastructure, foundational AI services and APIs, and packaging and upgrade capabilities – as well as breakthrough solutions across delivery intelligence, network automation, and edge computing. Our work spans classical ML, domain-specific language models, and Agentic AI.
Your Impact
As a Principal Machine Learning Engineer on Cisco’s CX AI Incubation and Agents team, you tackle ambiguous, high-impact challenges and lead cross-functional engagements from architecture and design through production and customer deployment. You will serve as the architectural and technical authority for designing, building, and scaling the AI foundation powering Cisco IQ and evolving customer needs. As a hands-on technical leader, you will design and build AI systems for production scale. You will set the benchmark for system design, platform governance, and technical excellence across the CX engineering ecosystem.
What You Will Own & Drive
- Foundational AI Platform Architecture: Design and build robust, multi-tenant AI services with scalable APIs, versioning, backward compatibility, and quota management across cloud, on-premises, and air-gapped environments.
- AI Technology Strategy and Execution: Select, evaluate, and implement models, frameworks, inference runtimes, and orchestration technologies. Translate emerging capabilities into production architectures optimized for scalability, latency, memory, and compute across GPU, CPU, and edge environments.
- AI Cost Optimization and Standards: Design and implement cost optimization across workloads by improving token efficiency, model selection, inference performance, and compute utilization. Establish measurable engineering standards for cost efficiency.
- Technical Governance & Leadership by Influence: Lead architecture and design reviews, resolve complex technical trade-offs, mentor senior engineers, and influence platform direction through hands-on technical leadership and execution.
Minimum Qualifications:
- Bachelors + 14 years of related experience, or Masters + 11 years of related experience, or PhD + 7 years of related experience.
- Experience developing, fine-tuning, and optimizing models in Python, PyTorch or JAX, using techniques such as PEFT or LoRA, quantization, and distillation.
- Experience architecting and deploying production LLM and/or SLM inference runtimes optimized with continuous batching, KV-cache management, or speculative decoding.
- Experience architecting and deploying production RAG systems and agentic workflows using vector databases.
- Experience designing and implementing automated evaluation frameworks for AI systems, including golden test datasets, LLM-as-a-judge methodologies, drift detection, and/or CI/CD regression gates.
- Experience architecting production AI platform APIs featuring robust quota management, versioning, and deployment across hybrid cloud and air-gapped environments.
Preferred Qualifications:
- Research & Thought Leadership: Recognized track record of industry contributions via publications, patents, conference presentations, or core contributions to open-source AI/ML projects.
- Edge & Resource-Constrained Inference: Hands-on experience optimizing inference workloads for resource-constrained compute environments (CPU, NPU, small GPU footprints, and on-prem hardware appliances).
Why Cisco?
At Cisco, we’re revolutionizing how data and infrastructure connect and protect organizations in the AI era – and beyond. We’ve been innovating fearlessly for 40 years to create solutions that power how humans and technology work together across the physical and digital worlds. These solutions provide customers with unparalleled security, visibility, and insights across the entire digital footprint.
Fueled by the depth and breadth of our technology, we experiment and create meaningful solutions. Add to that our worldwide network of doers and experts, and you’ll see that the opportunities to grow and build are limitless. We work as a team, collaborating with empathy to make really big things happen on a global scale. Because our solutions are everywhere, our impact is everywhere.
We are Cisco, and our power starts with you.
Message to applicants applying to work in the U.S. and/or Canada:
The starting salary range posted for this position is $296,300.00 to $374,800.00 and reflects the projected salary range for new hires in this position in U.S. and/or Canada locations, not including incentive compensation*, equity, or benefits.
Individual pay is determined by the candidate's hiring location, market conditions, job-related skillset, experience, qualifications, education, certifications, and/or training. The full salary range for certain locations is listed below. For locations not listed below, the recruiter can share more details about compensation for the role in your location during the hiring process.
U.S. employees are offered benefits, subject to Cisco’s plan eligibility rules, which include medical, dental and vision insurance, a 401(k) plan with a Cisco matching contribution, paid parental leave, short and long-term disability coverage, and basic life insurance. Please see the Cisco careers site to discover more benefits and perks. Employees may be eligible to receive grants of Cisco restricted stock units, which vest following continued employment with Cisco for defined periods of time.
U.S. employees are eligible for paid time away as described below, subject to Cisco’s policies:
- 10 paid holidays per full calendar year, plus 1 floating holiday for non-exempt employees
- 1 paid day off for employee’s birthday, paid year-end holiday shutdown, and 4 paid days off for personal wellness determined by Cisco
- Non-exempt employees** receive 16 days of paid vacation time per full calendar year, accrued at rate of 4.92 hours per pay period for full-time employees
- Exempt employees participate in Cisco’s flexible vacation time off program, which has no defined limit on how much vacation time eligible employees may use (subject to availability and some business limitations)
- 80 hours of sick time off provided on hire date and each January 1st thereafter, and up to 80 hours of unused sick time carried forward from one calendar year to the next
- Additional paid time away may be requested to deal with critical or emergency issues for family members
- Optional 10 paid days per full calendar year to volunteer
For non-sales roles, employees are also eligible to earn annual bonuses subject to Cisco’s policies.
Employees on sales plans earn performance-based incentive pay on top of their base salary, which is split between quota and non-quota components, subject to the applicable Cisco plan. For quota-based incentive pay, Cisco typically pays as follows:
- .75% of incentive target for each 1% of revenue attainment up to 50% of quota;
- 1.5% of incentive target for each 1% of attainment between 50% and 75%;
- 1% of incentive target for each 1% of attainment between 75% and 100%; and
- Once performance exceeds 100% attainment, incentive rates are at or above 1% for each 1% of attainment with no cap on incentive compensation.
For non-quota-based sales performance elements such as strategic sales objectives, Cisco may pay 0% up to 125% of target. Cisco sales plans do not have a minimum threshold of performance for sales incentive compensation to be paid.
The applicable full salary ranges for this position, by specific state, are listed below:
New York City Metro Area:
$296,300.00 - $431,000.00
Non-Metro New York state & Washington state:
$263,700.00 - $383,500.00
- For quota-based sales roles on Cisco’s sales plan, the ranges provided in this posting include base pay and sales target incentive compensation combined.
Employees in Illinois, whether exempt or non-exempt, will participate in a unique time off program to meet local requirements.
See all 2,321+ Machine Learning Engineer Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Machine Learning Engineer roles.
Get Access To All JobsTips for Finding Visa Sponsorship as a Machine Learning Engineer
Emphasize production engineering over research
MLE roles focus on deploying, scaling, and monitoring models in production - not just training them. Highlight experience with model serving frameworks like TensorFlow Serving, TorchServe, or Triton Inference Server to stand out.
Target companies with mature ML infrastructure teams
Google, Meta, Netflix, Uber, and Spotify have dedicated MLE teams that build and maintain production ML systems. These companies sponsor H-1B petitions under SOC 15-1252 and understand the engineering nature of the role.
Leverage your dual skill set in interviews
The MLE role bridges data science and software engineering, and that's your selling point. Strong candidates can discuss both model optimization and system design, which is rare and makes employers more willing to invest in sponsorship.
Build MLOps expertise to increase your value
Feature stores, experiment tracking, model monitoring, and automated retraining pipelines are critical MLE skills. Companies building serious ML products need engineers who can operationalize models, not just build prototypes.
Use STEM OPT to prove production reliability
With a STEM-eligible degree, you get up to 3 years of work authorization through OPT. ML systems require deep institutional knowledge to maintain - use that time to become indispensable to your team's production stack.
File under the right SOC code for engineering
MLE roles typically file under SOC 15-1252 (Software Developers), emphasizing the engineering and systems side of the work. This classification has strong precedent for H-1B approval - ensure your job description reflects the production engineering focus.
Frequently Asked Questions
What ML infrastructure skills are most valued by employers sponsoring machine learning engineers?
Experience with distributed training frameworks (PyTorch Distributed, DeepSpeed), model serving platforms (TensorFlow Serving, NVIDIA Triton, ONNX Runtime), and feature engineering tools (Feast, Tecton) are the most sought-after skills. Knowledge of GPU cluster management, inference cost optimization, and monitoring for data drift also carries significant weight. These specific technical requirements are exactly what make the visa petition strong, because they show the role requires specialized knowledge beyond general software engineering.
Do machine learning engineers need a PhD, or is a master's degree sufficient for sponsorship?
A master's degree is sufficient for the vast majority of ML engineering roles, and many positions only require a bachelor's in computer science or a related field. A PhD is more commonly expected for research-focused ML positions, not engineering roles focused on production systems. That said, a master's degree qualifies you for the additional 20,000 H-1B visa cap exemption slots reserved for U.S. advanced degree holders, which improves your lottery odds.
I have a research background but want to move into ML engineering. How does this affect sponsorship?
The transition is common and does not create visa issues. Your research background demonstrates the theoretical knowledge needed to make sound infrastructure decisions, while any production-adjacent work from your research (deploying models, building data pipelines, optimizing training runs) shows practical engineering capability. If you have a PhD, you benefit from the advanced degree H-1B exemption. The combination of theoretical depth from research and hands-on engineering skills can actually strengthen your petition.
How to find Machine Learning Engineer jobs with visa sponsorship?
To find Machine Learning Engineer jobs with visa sponsorship, use Migrate Mate, which specializes in connecting international talent with sponsoring employers. Focus on tech companies, startups, and research institutions that commonly hire ML engineers on H-1B, O-1 visa, or other work visas. These employers often need specialized AI/ML expertise and are willing to sponsor qualified candidates with relevant experience in data science, neural networks, and algorithm development.
Which companies sponsor machine learning engineers most actively?
Companies operationalizing ML at scale are the most active sponsors. This includes large tech firms (Google, Meta, Amazon, Microsoft), ML-first product companies (Spotify, Netflix, Uber, Stripe), and AI infrastructure startups (Databricks, Anyscale, Weights & Biases). Fintech and healthcare AI companies are also growing sponsors. Look for employers whose products depend on reliable ML systems in production, as they are most motivated to invest in sponsorship for engineers who can bridge the gap between a trained model and a live product.
What prevailing wage levels typically apply to ML engineering roles?
ML engineering salaries typically place candidates at Level 3 or Level 4 of the Department of Labor prevailing wage system, which is favorable for visa petitions. Higher wage levels signal to USCIS that the role is senior and specialized, reducing the risk of a Request for Evidence. If an employer offers a salary at Level 1, that is a red flag for both immigration risk and fair compensation. You can check prevailing wages for your role and location on the DOL's Foreign Labor Certification Data Center.
What is the prevailing wage requirement for sponsored Machine Learning Engineer jobs?
When a U.S. employer sponsors a foreign worker for a work visa, they are legally required to pay at least the "prevailing wage", the average wage paid to workers in the same occupation, in the same geographic area, with similar experience. This is set by the Department of Labor to prevent employers from hiring foreign workers at below-market rates. The prevailing wage varies significantly by role, location, and experience level. For example, a machine learning engineer in California will have a different prevailing wage than the same role in a smaller state. You can look up current prevailing wage rates for any occupation and location using the OFLC Wage Search Page.