Machine Learning Engineer
at Cisco Systems
San Jose, California, USA -
Start Date | Expiry Date | Salary | Posted On | Experience | Skills | Telecommute | Sponsor Visa |
---|---|---|---|---|---|---|---|
Immediate | 19 Jul, 2024 | Not Specified | 19 Apr, 2024 | 1 year(s) or above | Python,Communication Skills,Programming Languages,R | No | No |
Required Visa Status:
Citizen | GC |
US Citizen | Student Visa |
H1B | CPT |
OPT | H4 Spouse of H1B |
GC Green Card |
Employment Type:
Full Time | Part Time |
Permanent | Independent - 1099 |
Contract – W2 | C2H Independent |
C2H W2 | Contract – Corp 2 Corp |
Contract to Hire – Corp 2 Corp |
Description:
WHO WE ARE
The Cisco Security AI team delivers AI products and platform for all Cisco Secure products and portfolios so businesses around the world can defend against threats and safeguard the most vital aspects of their business with security resilience. We are passionate about making our customers secure by simplifying security with zero compromise using AI and Machine Learning.
BASIC QUALIFICATIONS
- 3+ years’ experience in programming languages such as Python or R, and experience with machine learning libraries (e.g., TensorFlow, PyTorch, scikit-learn).
- 2+ years’ experience building machine learning systems and scalable solutions.
- BA / BS degree with 2+ years of experience (or) MS degree with 1+ years of experience as a machine learning engineer.
PREFERRED QUALIFICATIONS
- Expertise in machine learning algorithms, deep learning, and statistical modeling.
- Excellent problem-solving and communication skills, with the ability to explain complex concepts to non-technical teammates.
Responsibilities:
In this role, you will tackle some of the most challenging issues facing businesses today. You will do this through:
Model Development: Develop and implement advanced ML models and algorithms to tackle security problems, including threat detection, anomaly detection, and risk assessment.
Model Training and Evaluation: Lead the training, validation, and fine-tuning ML models using current techniques and libraries. Define and track security-specific metrics for model performance.
Solution Development: Build robust software systems to integrate, deploy, and maintain advanced ML models in production environments. This includes developing and optimizing software frameworks, ensuring seamless model integration, and rigorously testing systems to maintain high reliability and performance standards.
Deployment Strategy: Collaborate with software engineering teams to design and implement deployment strategies for models into security systems, ensuring scalability, reliability, and efficiency.
Documentation and Best Practices: Establish an effective process for machine learning and security operations, and maintain clear documentation of models, data pipelines, and security procedures.
REQUIREMENT SUMMARY
Min:1.0Max:2.0 year(s)
Information Technology/IT
IT Software - Network Administration / Security
Software Engineering
BSc
Proficient
1
San Jose, CA, USA