Carrières chez Cisco

Meet the Team

You will be pivotal in contributing to the team responsible for designing and developing the next generation of scalable Kubernetes' infrastructure with machine learning platforms that support both traditional ML and state-of-the-art Large Language Models (LLMs). This is a position for experienced engineers where you will lead the technical direction, ensuring the performance, reliability, and scalability of AI systems while collaborating closely with data scientists, researchers, and other engineering teams.

Your Impact

You will take ownership of sophisticated ML pipelines, architect scalable infrastructure, and implement standard methodologies for Infrastructure as a Code with Golang along with MLOps. Your leadership will influence the adoption of modern technologies and processes while mentoring junior engineers to strengthen the team’s technical foundation. This role is perfect for someone with a deep passion for solving engineering challenges in the fast-paced AI/ML space, with a focus on delivering high-impact solutions at scale.

Core Responsibilities

As a Software Engineer with AI/ML Platform Experience you will:

• Architect and design scalable Kubernetes platforms supporting both traditional ML and Large Language Models (LLMs).
• Provide client support for hosting AI/ML workload on Kubernetes platform powered by GPU
• Lead the development of end-to-end ML pipelines, including data ingestion, model training, evaluation, and deployment.
• Drive AIOps initiative across Middleware platform by collaborating with multi-functional teams, including SRE, Software Engineers to operationalize and optimize ML models effectively.
• Define and implement MLOps standard methodologies such as monitoring, logging, and automated maintenance of models in production.
• Develop infrastructure automation tools and frameworks to improve efficiency across teams.
• Ensure platform reliability, scalability, and performance through meticulous engineering practices.
• Conduct code reviews, establish standard processes, and mentor junior engineers.
• Stay updated on the latest trends in AI/ML to influence platform enhancements.

Minimum Qualifications / Requirement -

• Experience: 5–7 years of software engineering experience, including at least 2+ years in machine learning-related roles.
• Expertise in Golang or Python, with hands-on experience with Kubernetes platform
• Along with ML frameworks (TensorFlow, PyTorch).
• Consistent track record in designing and deploying scalable machine learning systems in production.
• Deep understanding of ML algorithms, data pipelines, and optimization techniques.
• Experience building CI/CD pipelines for ML workflows, including model monitoring and retraining.
• Proficiency in cloud platforms and orchestration tools for distributed systems.
• Strong problem-solving and debugging skills for complex, large-scale systems.
• Experience in mentoring engineers and driving technical decision-making.

Preferred Qualifications / Requirements -

• Kubernetes and Container Orchestration:
• Sophisticated understanding in Kubernetes for managing production-grade systems and ensuring scalability.
• Sophisticated experience with Docker and orchestration of complex services.
• Software development:
• Expertise in Golang or Python
• Develop & enforce secure software development lifecycle
• MLOps Tools and Frameworks:
• Experience with architecting and optimizing workflows using Kubeflow pipelines, KServe, Airflow, and MLflow.
• Ability to design and implement efficient CI/CD pipelines for ML systems.
• Large Language Models (LLMs):
• Understanding of LangChain and experience designing RAG systems.
• Knowledge of integrating and scaling vector databases (e.g., Pinecone, FAISS) for real-world applications.
• Distributed Systems and Microservices:
• Consistent record of designing and leading the development of distributed systems.
• Experience with implementing robust inter-service communication patterns and solving scalability issues.

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