Software Technical Lead, Cisco Meraki

• Bachelors 12-plus years of related experience, or Masters 8-plus years of related experience, or PhD 5-plus years of related experience
• Core MLOps & Infrastructure Skills : End-to-End MLOps Pipelines, Model Deployment & Serving, Model Monitoring & Observability, CI/CD for MLOps
• Cloud & Infrastructure : Cloud Platforms (AWS, GCP, or Azure), Containerization & Orchestration (Docker / K8s), Infrastructure as Code (IaC) – Terraform, CloudFormation, Networking & Security – VPCs, IAM, API Gateways, role-based access control (RBAC)
• Data & Feature Engineering : Data processing platforms like Apache Kafka, Flink, Spark, Kinesis, etc; data lakes like SQL/No SQL stores, Snowflake, etc and ML libraries such as Pandas, Scikit-Learn, Tensorflow, Keras, etc
• Experience in working with GPU Scheduling and Orchestration architecture as well as debugging accelerators like GPU/TPU/etc
• Experience maintaining scalable MLOps platforms and supporting production systems to minimize customer downtime
• Strong written and verbal communication skills and excellent attention to detail and accuracy
• Problem Solving and Critical thinking with focus on reliability and incident management

Desirable

• The Data Science Infrastructure team is a growing group that works closely with executives and leaders across the company to support the development and alignment on our business strategy. We are looking for a Software Technical Lead, Machine Learning Engineer focusing on MLOps infrastructure to build a next generation cloud-based analytics platform to solve performance and connectivity issues in enterprise environments
• Meraki's cloud-managed model offers a unique opportunity to draw upon data from hundreds of thousands of networks and millions of access points deployed across our wide ranging customer base.
• The goal is to apply the rich telemetry data available from these devices and combine it with the AI and the cloud to build an analytics engine that can provide intuitive, yet detailed insights into the performance issues across our customer networks. Given the scale of Meraki’s deployment, this provides a unique engineering opportunity to build an impactful solution that can help enhance our customer experience at large
• Help to define and implement the Cisco Network Platform data science infra team's AI/ML priorities while collaborating with product managers, AI architects, designers, user researchers and engineering partners
• Explore, design and implement advanced ML Infrastructure framework and tools
• Establish standard methodologies for model integration, deployment, and monitoring using CI/CD principles
• Evaluate the performance of AI models and systems through meticulous testing, online and offline experimentation, and benchmarking
• Use your ingenuity and creativity to resolve complicated and/or novel product and engineering challenges
• Influence architectural decisions with a focus on security, scalability, and high-performance
• Collaborate with data science and full stack teams across the Cisco Network Platform organization to define and build features across the product portfolio
• Work with multi-functional partners to establish team priorities and lead those engagements
• Mentor senior and mid-career team members by providing technical guidance

Total funding: $80m

Cisco Meraki, formed from the acquisition of Meraki by Cisco in 2012, is an industry-leading cloud-managed IT company. Its technology provides unified management of mobile devices, Macs, PCs, and entire networks, all from a centralised dashboard.