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Software Engineer Data​/AI​/Systems

Job in San Francisco, San Francisco County, California, 94199, USA
Listing for: Info Resume Edge
Full Time position
Listed on 2026-02-16
Job specializations:
  • IT/Tech
    Cloud Computing, AI Engineer
Salary/Wage Range or Industry Benchmark: 200000 - 250000 USD Yearly USD 200000.00 250000.00 YEAR
Job Description & How to Apply Below
Position: Software Engineer Data/AI/Intelligent Systems

Cisco is a leading technology company focused on revolutionizing data and infrastructure in the AI era. The role involves developing scalable data pipelines and building analytics platforms to support machine learning initiatives, enabling Ciscos business groups to leverage AI for operational excellence.

Responsibilities
  • Develop scalable data pipelines
  • Design robust analytics platforms
  • Build infrastructure to support machine learning initiatives
  • Solve complex challenges with innovation and attention to detail
  • Build and maintain key software tools and platforms
Required
  • Completion within the past 3 years, or current enrollment with expected completion within 12 months, of a certification or relevant degree program (e.g., Associates, Apprenticeship, Boot Camp, or Certification in a specialized program + 1 year of relevant experience, High School Diploma + 2 years of relevant experience) or Bachelors + 0 years of relevant experience
  • Proficiency in Python, with a strong understanding of fundamental data structures
  • Hands-on experience with machine learning frameworks such as Tensor Flow, PyTorch, or scikit-learn
  • Familiarity with distributed data processing technologies, including Apache Spark, Hadoop (Map Reduce), or Apache Flink
  • Experience with containerization and orchestration tools, such as Docker and Kubernetes, for deploying data and machine learning workloads
Preferred
  • Hands-on experience with AI/ML
  • Familiarity with major cloud platforms, such as AWS, Azure, or Google Cloud
  • Understanding of distributed systems concepts, including scalability, reliability, fault tolerance, and data consistency, as well as familiarity with distributed computing patterns (e.g., load balancing, consensus algorithms, and inter-service communication)
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