Cisco Software Engineer 

India, Karnataka, Bengaluru 

254711762

You will join a fast-paced, innovative team responsible for building cutting-edge machine learning platforms and pipelines. This role offers a phenomenal opportunity to grow your engineering skills while working with modern technologies in Kubernetes as well as AI/ML ecosystem. You will focus on implementing robust, scalable, and efficient machine learning systems in collaboration with senior platform engineers.

The ideal candidate has a strong foundation in software development and a keen interest in machine learning operations (MLOps). You will contribute to the development of pipelines, frameworks, and infrastructure, helping bring Kubernetes Platform as well as machine learning infrastructure to production seamlessly. With access to senior mentors and a collaborative environment, this position is ideal for engineers looking to deepen their Software Skill with Golang / Python, Platform engineering skills with K8 platforms & deepen their learning in AI and ML systems.

As a
Software Engineer with focus on AI infrastructure platform development, you will:

• Develop Code to run Infrastructure as a Code
• Follow SDLC best practices for deployment on Kubernetes platform
• Implement components of machine learning pipelines, including training, evaluation, and deployment of models.
• Collaborate with team optimize ML models for AI OPs adoption for Kubernetes platform with plug & play solution
• Assist in implementing MLOps practices such as monitoring, logging, and scaling pipelines.
• Write clean, efficient, and maintainable code for IaaC as well as ML-related systems and frameworks.
• Ensure quality and reliability of ML workflows through unit testing and integration testing.
• Perform operations no Kubernetes platform along with regular OnCall & client engagement

Minimum Qualifications / Requirement -

• Experience : 2–4 years of software engineering experience, including exposure to machine learning workflows.
• Proficiency in GoLang or Python and experience with ML frameworks like TensorFlow or PyTorch.
• Familiarity with CI/CD pipelines, version control systems (e.g., Git), and containerization tools like Docker.
• Basic understanding of ML algorithms, concepts, and deployment practices.
• Strong problem-solving and debugging skills with guidance from senior team members.
• Ability to collaborate within agile teams using tools like JIRA.

Preferred Qualifications / Requirements -

• Kubernetes and Container Orchestration:
• Familiarity with Kubernetes for deploying containerized applications.
• Basic experience with containerization tools like Docker.
• Understanding of Infrastructure as a Code
• MLOps Tools and Frameworks:
• Experience with Kubeflow pipelines and KServe.
• Familiarity with Airflow for workflow orchestration and MLflow for tracking experiments.
• Software development:
• Hand-on experience in Golang or Python
• Develop with SOLID principles
• Large Language Models (LLMs):
• Basic understanding of LangChain, RAG, and vector databases.
• Experience in integrating LLMs or embeddings into smaller-scale applications.
• Distributed Systems and Microservices:
• Hands-on implementation of microservices.
• Understanding distributed systems design.