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Machine Learning Engineer Master's (Intern)- India Engineering/ Splunk / UHR

CiscoHyderabad, Telangāna, IndiaIndia6d ago
onsiteinternshipentry
192 views130 applicants
💼 Competitive Salary

Job Description

At Cisco, AI isn’t just a technology—it’s a movement. Our AI teams are shaping the future by embedding intelligence into collaboration, networking, security, observability, and beyond. Our teams focus on building next-generation businesses powered by AI. We are a forward-thinking team of engineers, researchers, and innovators working at the intersection of deep learning, generative AI, and cutting-edge product design. The vibe is fast-paced, entrepreneurial, and collaborative, where every day offers the opportunity to create meaningful solutions with massive global impact. Your Impact As a Machine Learning Engineer, you will be at the forefront of Cisco’s generative AI strategy. You will design, train, and optimize large language models (LLMs) and multimodal AI systems to address ambitious real-world challenges across industries. You will drive innovation by developing scalable, high-performing AI solutions, collaborating across engineering and product teams, and guiding research into emerging technologies. Success in this role means delivering impactful AI capabilities that transform Cisco’s products and customer experiences while mentoring peers and evangelizing AI innovation both inside and outside the company. Minimum Qualifications Students graduating in 2027 Programming experience with Java, C++, Python, or related languages Hands-on experience in natural language processing, computer vision, or multimodal interaction. Experience using deep learning frameworks to train, fine-tune, and optimize GenAI models for performance and scalability. Experience designing and deploying proof-of-concepts and production-ready AI systems. Preferred Qualifications Strong background in system design, software development, and production deployment at scale. Ability to transform ambiguous requirements into actionable deep learning solutions. Familiarity with state-of-the-art models and methods (e.g., CLIP, DALLE 2, diffusion models). Demonstrated contributions to the AI/ML community through top-tier publications, open-source projects, or leaderboard competitions.

Requirements

  • into actionable deep learning solutions.
  • Familiarity with state-of-the-art models and methods (e.g., CLIP, DALLE 2, diffusion models).
  • Demonstrated contributions to the AI/ML community through top-tier publications, open-source projects, or leaderboard competitions.

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