Machine Learning Visa Sponsorship Jobs in California
California is the top state for machine learning visa sponsorship jobs, with major employers including Google, Meta, Apple, and NVIDIA headquartered here. The San Francisco Bay Area and Los Angeles drive most hiring, alongside a deep university pipeline from Stanford and UC Berkeley feeding world-class ML research and engineering talent into industry.
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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.
Machine Learning Job Roles in California
See all 858+ Machine Learning Jobs in California
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Search Machine Learning Jobs in CaliforniaMachine Learning Jobs in California: Frequently Asked Questions
Which companies sponsor visas for machine learning roles in California?
The most active sponsors for machine learning roles in California include Google, Meta, Apple, Microsoft, Amazon, NVIDIA, Salesforce, and Adobe, concentrated primarily in the Bay Area and Los Angeles. Semiconductor and AI chip companies like NVIDIA and Qualcomm also file significant numbers of sponsorships. Mid-size AI startups in San Francisco and Palo Alto round out the sponsoring employer base for ML engineers and researchers.
Which visa types are most common for machine learning roles in California?
The H-1B visa is by far the most common visa for machine learning roles in California, as ML engineering and research positions typically meet the specialty occupation requirement. Candidates with extraordinary recognition in the field may qualify for the O-1A. Australian citizens can use the E-3 visa as an H-1B alternative. Some roles at universities or national labs may fall under J-1 visa or F-1 OPT, particularly for recent graduates.
Which cities in California have the most machine learning sponsorship jobs?
The San Francisco Bay Area, including San Jose, Sunnyvale, Mountain View, Palo Alto, and San Francisco itself, accounts for the majority of machine learning sponsorship jobs in California. Los Angeles has grown substantially, driven by entertainment technology, healthcare AI, and a strong startup ecosystem. San Diego also contributes, particularly through biotech and defense-adjacent AI applications at companies like Qualcomm.
How to find machine learning visa sponsorship jobs in California?
Migrate Mate is built specifically for international job seekers targeting visa sponsorship roles, including machine learning positions across California. You can filter by state and role to surface employers with a documented history of sponsoring ML engineers and researchers in the Bay Area, Los Angeles, and beyond. Because sponsorship willingness varies widely by employer and role type, focusing on verified sponsors saves significant time in a competitive field.
Are there any California-specific considerations for machine learning visa sponsorship?
California's high cost of living means H-1B prevailing wage requirements in cities like San Francisco and San Jose sit at the upper end of national ranges for machine learning roles, which can actually work in candidates' favor since employers must meet those wage floors. The state's dense concentration of AI-focused companies and proximity to Stanford, UC Berkeley, and UCLA also creates a university-to-industry pipeline that keeps sponsorship activity consistently high compared to most other states.
What is the prevailing wage for sponsored machine learning jobs in California?
U.S. employers sponsoring a visa must pay at least the prevailing wage, which is what workers in the same role, area, and experience level typically earn. The Department of Labor sets this rate to make sure companies aren't hiring foreign workers simply because they'd accept lower pay than a U.S. worker. It varies by job title, location, and experience. You can look up current prevailing wage rates for any occupation and location using the OFLC Wage Search page.