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Role:
As the Senior Principal Applied Scientist in the Artificial Intelligence group, you will be a key player in defining and executing the technical roadmap for the team, as we develop 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 end-to-end product development lifecycle from ideation to production.
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 with product managers to translate the business and product requirements into concrete objectives for 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.
- Collaborate with fellow technical leaders to ensure the successful and timely delivery of AI/ML models and service integration.
- 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.
- Develop production code and advocate for the best coding and engineering practices.
- Participate in project planning, review, and retrospective sessions.
- Identify and mitigate risks in our plans and executions, especially at the intersection of business and engineering.
Requirements:
Knowledge, Skills, and Abilities:
- PhD in Computer Science or a related field with at least 10 years of experience OR MS in Computer Science or related field with at least 15 years of industry experience.
- Demonstrated experience in leading impactful AI product development at scale.
- Deep understanding of ML frameworks (e.g., TensorFlow, PyTorch) and programming languages commonly used in AI research.
- 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 them in production systems.
- Experience large-scale data processing and parallel computing – GPU, multi-GPU and distributed training.
- Commitment to staying up-to-date with the field and applying academic advances to solve complex business problems, and bringing them into production.
- Strong problem-solving skills and the ability to translate research insights into practical solutions that address real-world challenges.
- Excellent communication skills with the ability to articulate complex technical concepts to both technical and non-technical audiences.
- Experience in mentoring and guiding junior researchers or team members.
- Experience in the Cybersecurity and/or Observability industry is preferred.