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Applied AI Scientist

Applied AI Scientist

Cisco

2 - 7 years

20 - 25 Lacs

hyderabad bengaluru

Posted:1 day ago| Platform:

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Skills Required

ai mlops python networking research analytics cloud deep learning tensorflow nlp data science pytorch splunk ai research observability cisco language models customer experience ml

Work Mode

Work from Office

Job Type

Full Time

Job Description

Meet the Team

Splunk, a Cisco company, is building a safer, more resilient digital world with an end to end, full stack platform designed for hybrid, multi cloud environments. Join the Foundational Modeling team at Splunk, where we advance the state of AI for high volume, real time, multi modal machine generated data including logs, time series, traces, and events. We combine deep AI research expertise with the scale and operational excellence of Splunk and Cisco s global engineering capabilities. Our work spans networking, security, observability, and customer experience designing and deploying foundation models that enhance reliability, strengthen security, prevent downtime, and deliver predictive insights across Splunk Observability, Security, and Platform at enterprise scale. You ll be part of a culture that values technical excellence, impact driven innovation, and cross functional collaboration all within a flexible, growth oriented environment.

Your Impact

Own and develop specific components of foundation-model pipelines for machine-generated data primarily logs, with supporting work across time series, traces, and events.
Implement and optimize parts of distributed training and inference workflows, including profiling, scaling, and efficiency improvements.
Collaborate with engineering, product, and data science teams to translate requirements into workable prototypes and support production integration.
Participate in team knowledge-sharing, documentation, and internal technical discussions to help strengthen collective expertise.
Stay current with emerging AI/ML advances and bring relevant ideas, papers, and techniques into ongoing research and development.

Minimum Qualifications:

PhD in Computer Science or related quantitative field, or Master plus 2+ years of industry research experience.
Proven track record in at least one of the following areas: large language modeling for both structure and unstructured data, deep learning based time series modeling, advanced anomaly detection, and multi-modality modeling.
Solid proficiency in Python and deep learning frameworks (e.g., PyTorch, TensorFlow)
Experience translating research ideas into production systems.

Preferred Qualifications:

Deep NLP & Domain Adapted LLMs: Background in building and adapting large scale language models (e.g., T5, BERT, LLaMA) for specialized domains including structured/unstructured logs, text, and event sequences.
Log Analytics Expertise In depth knowledge of structured/unstructured system logs, event sequence analysis, anomaly detection, and root cause identification.
Advanced Anomaly Detection Experience creating robust, scalable approaches (statistical, deep learning, or hybrid) for high volume, real time logs data.
Multi Modal AI Modeling Strong track record fusing logs, time series, traces, tabular data, and graphs for foundation models tackling complex operational insights.
Large Scale Training & Optimization Experience optimizing model architectures, distributed training pipelines, and inference efficiency to minimize cost and latency while preserving accuracy.
MLOps & Continuous Learning Fluency in automated retraining, drift detection, incremental updates, and production monitoring of ML models.
Strong Research Track Record Publications in top AI/ML conferences or journals (e.g., NeurIPS, ICML, ICLR, AAAI, CVPR, ACL, KDD) demonstrating contributions to state of the art methods and real world applications.

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Applied AI Scientist