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About the Role
Lead research on world models and learning-based approaches for autonomous networks, developing models that understand network dynamics, predict behavior, and enable optimization and troubleshooting.
Responsibilities
- Develop world models that learn the state and dynamics of large-scale network environments.
- Build models that predict network behavior and the impact of configuration and operational changes.
- Develop model-based reinforcement learning approaches for network optimization, troubleshooting, and remediation.
- Build simulation environments for training and evaluating models and agents before they operate on production networks.
- Explore new approaches to representation learning, planning, and sequential decision-making for network environments.
- Develop methods to evaluate the reliability and safety of learned policies before deployment.
- Work with networking experts and engineers to evaluate research on real network data and systems.
- Publish research at leading AI/ML conferences and contribute to open-source projects.
Requirements
- Masters in Computer Science, Machine Learning, Artificial Intelligence, Robotics, Autonomous Systems, or a related field, with 8+ years of relevant research experience, or equivalent demonstrated research impact.
- Research experience in one or more of world models, reinforcement learning, model-based RL, representation learning, planning, or sequential decision-making.
- 3+ years of hands-on experience building, training, and optimizing deep learning models using PyTorch, JAX, or comparable frameworks, including at least 2 models trained and evaluated at production or research scale.
- Demonstrated track record of research through publications at leading AI/ML conferences or equivalent research contributions.
- Ability to take a research problem from an idea through experimentation and working prototype.
Skills
- PyTorch
- JAX
- Deep Learning Models
- World Models
- Reinforcement Learning
- Model-based RL
- Representation Learning
- Planning
- Sequential Decision-Making
- Graph Learning
- Complex Dynamic Systems Modeling
- Networking
- Distributed Systems
- Robotics
- Autonomous Systems
- Embodied AI
Location
- U.S.
- Canada
- New York City Metro Area
- Non-Metro New York state
- Washington state
Work Type
- Full-time
Experience Level
- Principal
- 8+ years of relevant research experience
- 3+ years of hands-on experience building, training, and optimizing deep learning models
Education Level
- Masters in Computer Science, Machine Learning, Artificial Intelligence, Robotics, Autonomous Systems, or a related field
Salary/Compensations
- $296,300.00 - $374,800.00 (U.S. and/or Canada)
- $296,300.00 - $431,000.00 (New York City Metro Area)
- $263,700.00 - $383,500.00 (Non-Metro New York state & Washington state)
Benefits
- Medical insurance
- Dental insurance
- Vision insurance
- 401(k) plan with Cisco matching contribution
- Paid parental leave
- Short-term disability coverage
- Long-term disability coverage
- Basic life insurance
- 10 paid holidays per full calendar year
- 1 floating holiday for non-exempt employees
- 1 paid day off for employee’s birthday
- Paid year-end holiday shutdown
- 4 paid days off for personal wellness
- 16 days of paid vacation time per full calendar year (non-exempt employees)
- Flexible vacation time off program (exempt employees)
- 80 hours of sick time off provided on hire date and each January 1st thereafter
- Up to 80 hours of unused sick time carried forward
- Additional paid time away for critical or emergency family issues
- Optional 10 paid days per full calendar year to volunteer
- Annual bonuses (non-sales roles)
- Performance-based incentive pay (sales roles)
- Grants of Cisco restricted stock units
About the Company
- Cisco is revolutionizing how data and infrastructure connect and protect organizations in the AI era.
- Innovating for 40 years to create solutions that power how humans and technology work together across physical and digital worlds.
- Solutions provide customers with unparalleled security, visibility, and insights across the entire digital footprint.
- Experimenting and creating meaningful solutions fueled by technology depth and breadth.
- Worldwide network of doers and experts offering limitless opportunities to grow and build.
- Working as a team, collaborating with empathy to make significant global impact.