Join us as we pursue our disruptive new vision to make machine data accessible, usable and valuable to everyone. We are a company filled with people who are passionate about our product and seek to deliver the best experience for our customers.
At Splunk, we’re committed to our work, customers, having fun and most importantly to each other’s success. Learn more about Splunk careers and how you can become a part of our journey!Role : As a Senior Applied Scientist in the Artificial Intelligence group, you will be responsible for developing the core AI / ML capabilities to power the entire Splunk product portfolio and help our customers to drive their journey to digital resiliency.
You will collaborate with cross-functional teams, mentor junior team members, and help drive the scientific roadmap of the area.
Responsibilities : The responsibilities of this role include :
- Lead the development of core AI / ML models and algorithms that drive our product’s key use cases in the cybersecurity and observability domains.
- Collaborate closely with software engineers, applied scientists, and product managers to integrate generative AI solutions into our products and services.
- Stay up to date with the latest research and developments in the field of AI / ML, and ensure that these advancements are properly incorporated into our technology roadmap.
- Provide technical guidance and mentorship to team members to ensure the development of their skills.
- Actively participate in cross-functional discussions and strategic decisions related to AI research directions and product roadmaps.
Requirements : Knowledge, Skills, and Abilities :
- PhD in Computer Science or a related field with at least 1 years of experience OR MS in Computer Science or related field with at least 3-4 years of industry experience
- Experience training and fine tuning LLMs
- Experience with time series anomaly detection
- In-depth knowledge and proven track record in AI / ML technology, including deep learning, time series modeling, natural language processing, and unsupervised learning.
- In-depth knowledge and proven track record in Generative AI technology and Large Language Models (LLM).
- Experience developing large-scale, complex models and deploying and taking them from research to production systems.
- Strong problem-solving skills and the ability to translate research insights into practical solutions that address real-world challenges.
- Deep understanding of ML frameworks (e.g., TensorFlow, PyTorch) and programming languages commonly used in AI research.
- Excellent communication skills with the ability to articulate complex technical concepts to both technical and non-technical audiences.
- Experience in the Cybersecurity and / or Observability industry is preferred.
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