1

Cisco Machine Learning Jobs (NOW HIRING)

... Cisco through invited talks and technical collaborations. Minimum Qualifications * PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related technical field, plus 5+ years of ...

... Cisco through invited talks and technical collaborations. Minimum Qualifications * PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related technical field, plus 5+ years of ...

AI, Machine Learning, or developer platforms experience. * Experience with programming language ... Why Cisco? At Cisco, we're revolutionizing how data and infrastructure connect and protect ...

AI, Machine Learning, or developer platforms experience. * Experience with programming language ... Why Cisco? At Cisco, we're revolutionizing how data and infrastructure connect and protect ...

Principal AI Researcher

San Francisco, CA · On-site

$296K - $374K/yr

Masters in Computer Science, Machine Learning, Artificial Intelligence, Robotics, Autonomous ... Why Cisco? At Cisco, we're revolutionizing how data and infrastructure connect and protect ...

New

Become known as a thought-leader in machine learning and predictive analytics. * Expand ... Why Cisco? At Cisco, we're revolutionizing how data and infrastructure connect and protect ...

Account Executive - Splunk (Remote)

Topeka, KS · On-site +1

$308K - $389K/yr

Become known as a thought-leader in machine learning and predictive analytics. * Expand ... Why Cisco? At Cisco, we're revolutionizing how data and infrastructure connect and protect ...

next page

Showing results 1-20

Cisco Machine Learning information

See salary details

$90

$94

$100

How much do cisco machine learning jobs pay per hour?

As of Aug 22, 2026, the average hourly pay for cisco machine learning in the United States is $94.95, according to ZipRecruiter salary data. Most workers in this role earn between $92.79 and $96.15 per hour, depending on experience, location, and employer.

What is a Cisco machine learning engineer?

A Cisco Machine Learning Engineer is a professional who designs, develops, and implements machine learning models and solutions within Cisco's ecosystem. They work with large data sets to build algorithms that improve products and services such as network security, automation, and analytics. Their role often involves collaborating with software engineers, data scientists, and product teams to integrate intelligent features into Cisco's hardware and software offerings. These engineers are proficient in programming, data analysis, and have a strong understanding of networking concepts relevant to Cisco technologies.

What are the key skills and qualifications needed to thrive as a Cisco machine learning engineer?

To thrive as a Cisco Machine Learning Engineer, you need strong skills in data science, programming (Python, R), and a solid understanding of machine learning algorithms, often supported by a degree in computer science, engineering, or a related field. Familiarity with Cisco technologies, cloud platforms, and tools like TensorFlow, PyTorch, and relevant certifications (e.g., Cisco DevNet) are typically required. Analytical thinking, problem-solving, and effective communication are essential soft skills for collaborating on complex projects and translating technical findings. These skills are crucial for developing, deploying, and optimizing machine learning solutions that drive innovation and business value within Cisco environments.

What are some common challenges faced by Cisco machine learning engineers when deploying models in a production environment?

Cisco Machine Learning engineers often encounter challenges such as ensuring model scalability to handle large volumes of network data, integrating models with existing infrastructure, and maintaining real-time performance. Security and data privacy are also critical concerns, given the sensitivity of network data. Collaboration with cross-functional teams—including network engineers, DevOps, and security specialists—is essential to address these challenges and ensure successful deployment and ongoing management of ML solutions.

What is the difference between Cisco Machine Learning vs Cisco Data Scientist?

AspectCisco Machine LearningCisco Data Scientist
Required CredentialsBachelor's or higher in CS, ML, or related fields; certifications like Cisco CCNA/CCNP may be beneficialBachelor's or higher in Data Science, Statistics, or related; often includes certifications in data analysis or programming
Work EnvironmentNetwork infrastructure, cybersecurity, and enterprise solutions within Cisco environmentsData analysis, modeling, and insights within Cisco's business and product data
Employer & Industry UsagePrimarily in networking, cybersecurity, and enterprise solutionsAcross data-driven projects, product development, and analytics teams

While both roles involve working with data and require technical skills, Cisco Machine Learning focuses on developing ML models for network and security solutions, whereas Cisco Data Scientists analyze data to inform business decisions. The roles often overlap but differ in their primary focus and application within Cisco's ecosystem.

More about Cisco Machine Learning jobs

What states have the most Cisco Machine Learning jobs?

States with the most job openings for Cisco Machine Learning jobs include:

Infographic showing various Cisco Machine Learning job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 23% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $197,499 per year, or $95 per hour.

Lead Machine Learning Engineering, (Hybrid)

Cisco

San Jose, CA

$120K - $158K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 7 days ago


Cisco Systems rating

8.0

Company rating: 8.0 out of 10

Based on 42 frontline employees who took The Breakroom Quiz

59th of 159 rated electronics manufacturers


Job description

The application window is expected to close on: 09/28/2026

Job posting may be removed earlier if the position is filled or if a sufficient number of applications are received.

This is a hybrid role based out of Cisco's Seattle or San Jose office.Meet the Team

The Cisco AI Research team brings together AI researchers, machine learning engineers, data engineers, and networking domain experts to build the next generation of AI-powered networking.

We work at the intersection of generative AI, large-scale data systems, and networking, developing Large Language Models (LLMs), agents, and domain-specific AI systems. Our work spans research and engineering, with a strong focus on translating advances in AI into scalable systems and real-world impact.

Your Impact

As a Lead Machine Learning Engineer, you will build and improve the data and ML systems that power our LLMs and AI models.

A major focus of this role is solving one of the most important challenges in modern AI: creating high-quality training and evaluation data at scale. You will design and build scalable data pipelines, improve human data labeling workflows, create synthetic datasets, and develop automated approaches for continuously measuring and improving dataset quality.

This is a hands-on technical role at the intersection of machine learning engineering and data engineering. You will work closely with researchers, engineers, and domain experts to determine what data our models need, how to create it efficiently, and how to measure its impact on model performance.

  • Design, build, and maintain robust, scalable data pipelines that support the full lifecycle of ML and LLM development, from initial data ingestion to production-ready model deployment.

  • Architect and manage human-in-the-loop labeling workflows, including task generation, quality control, and feedback integration to ensure high-fidelity training data.

  • Develop scalable strategies for synthetic data generation, filtering, and validation to enhance dataset diversity, coverage, and overall quality.

  • Leverage LLMs and advanced ML techniques to automate data generation, labeling, scoring, and evaluation processes, increasing efficiency and consistency.

  • Establish rigorous systems to measure and mitigate dataset failure modes-such as bias, contamination, and distribution shifts-while designing experiments that directly link dataset composition to model performance.

  • Collaborate closely with researchers and ML engineers to define dataset requirements for fine-tuning, preference learning, and agent development, ensuring alignment with project goals.

  • Provide technical direction on infrastructure, compute, and storage decisions while fostering engineering excellence through design reviews, best practices, and team mentorship.

Minimum Qualifications
  • Bachelor's degree in a STEM field with 8+ years of relevant experience, OR Master's degree in a STEM field with 6+ years of relevant experience, OR PhD in STEM or a relevant technical field with 3+ years of industry or academic research experience.

  • 3+ years of hands-on experience building, curating, and scaling datasets for machine learning training and evaluation.

  • 5+ years of professional programming experience using Python, C++, or Go within a production or research environment.

  • 5+ years of experience using machine learning frameworks such as PyTorch, TensorFlow, or equivalent technologies to develop, train, evaluate, and deploy machine learning models.

Preferred Qualifications
  • Expertise in curating, scaling, and managing datasets for the entire LLM lifecycle-including synthetic data generation, augmentation, and post-training workflows like SFT and RLHF.

  • Proficiency in designing human-in-the-loop labeling systems and proactively mitigating complex dataset failure modes such as label noise, bias, contamination, and distribution shift.

  • Demonstrated success using LLMs for data generation, model-assisted labeling, and evaluation, with a focus on connecting iterative dataset changes to measurable improvements in model performance.

  • Strong technical foundation in distributed data processing frameworks (e.g., Spark, Ray, Beam) and the ability to architect and deploy complex data engineering projects into production.

  • A research-engineering mindset that bridges the gap between experimentation and production, combined with the communication skills to influence researchers, engineers, and product stakeholders.

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 $197,500.00 to $249,800.00 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 ofunused sick timecarried forwardfrom one calendar yearto 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:

$216,300.00 - $322,900.00

Non-Metro New York state & Washington state:

$197,500.00 - $287,300.00

* 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.


What Cisco Systems employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


Cisco Systems logo

About Cisco Systems

Sourced by ZipRecruiter

Cisco Systems, a global tech titan based in San Jose, CA, US, operates in the information technology and services industry. Founded in 1984, the company was derived from a project between two computer scientists from Stanford University. They aimed to connect different networks of computer systems at the university, resulting in the first multi-protocol router, and subsequently, the birth of Cisco. As an industry-leading manufacturer of networking hardware and telecommunications equipment, Cisco's product and services range includes routers, switches, firewall devices, and telecommunication technology. The company's mission, "to shape the future of the Internet by creating unprecedented value and opportunity for our customers, employees, investors, and ecosystem partners," is a testament to its pursuit of technology-forward innovation and customer satisfaction.

Industry

Computer and computer peripheral equipment and software wholesalers

Company size

10,000+ Employees

Headquarters location

San Jose, CA, US

Year founded

1984

Social media