Principal Machine Learning Engineer Full-time

Description

Join us as we pursue our exciting 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 are 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!

Overview
As a Principal Machine Learning Engineer in the Artificial Intelligence group, you will be hands-on in developing and driving the core AI/ML capabilities that power the entire Splunk product portfolio. You will focus on building scalable, production-grade models, algorithms, and tools that form the backbone of our AI-driven product features. Collaborating with cross-functional teams, you will play a pivotal role in shaping the AI engineering landscape, with a strong emphasis on the application of cutting-edge research and practical deployment.

Responsibilities

• Develop Core AI Engineering Capabilities: Design and implement AI/ML models and algorithms that drive critical use cases across Splunk’s product offerings, with a focus on scalability, performance, and real-world applicability. Your work will span areas such as deep learning, natural language processing, time series modeling, and unsupervised learning.
• Build Production-Ready AI Systems: Take a hands-on role in the development and deployment of AI systems at scale. You’ll be responsible for building robust, maintainable, and efficient ML systems that run in production environments, ensuring seamless integration with existing product workflows.
• Build Production-Ready AI Agents: Design, implement, and fine-tune conversational AI solutions, including chatbots and virtual assistants, leveraging natural language processing (NLP), dialogue management systems, and large language models (LLMs). Optimize user interactions, ensuring accuracy, relevance, and an intuitive conversational flow to enhance customer engagement and satisfaction.
• Research and Innovation: Stay at the forefront of AI/ML developments, incorporating cutting-edge research into practical, applied solutions. Investigate and integrate new methodologies, such as advancements in generative AI and large language models (LLMs), into our product ecosystem.
• Collaborate Across Teams: Partner with cross-functional teams including product managers, data scientists, and software engineers to align AI/ML engineering efforts with business goals. Ensure a clear, iterative approach to building AI-powered product features.
• Drive Technical Vision: Define and drive the technical strategy for AI/ML in our product suite, collaborating with product leads and other engineering teams to align on the vision, goals, and roadmap. Focus on building flexible, scalable, and maintainable systems that enable ongoing innovation and improvements.
• Mentorship and Skill Development: While this is a hands-on engineering role, you will also mentor and guide junior engineers, fostering a culture of learning and growth within the team.
• Lead by Example: Serve as a role model in coding practices, technical design, and problem-solving. Provide technical leadership and guidance across complex projects, setting high standards for engineering excellence.

Requirements

• In-depth AI/ML Expertise: Extensive experience and expertise in machine learning, deep learning, and statistical modeling, with a focus on large-scale deployment.
• Hands-on Engineering Experience: Proven track record of building and deploying production-grade AI/ML systems. Strong proficiency in one or more machine learning frameworks (e.g., TensorFlow, PyTorch) and the full stack of engineering tools required for large-scale ML (e.g., cloud infrastructure, version control, containerization).
• Generative AI and LLM Expertise: Significant experience working with generative AI models, large language models (LLMs), and other state-of-the-art AI technologies, and integrating them into enterprise-level applications.
• Conversational AI Expertise: Proven experience in building and deploying conversational AI systems, including natural language processing (NLP), intent recognition, and dialogue management. Expertise in designing RAG pipelines and implementing guardrails to ensure robust, secure, and ethical chatbot interactions. Familiarity with frameworks for chatbot development and optimization, with a focus on scalability and user experience.
• Coding and Algorithm Development: Proficiency in modern programming languages such as Python, Java, or C++. Strong algorithmic skills and experience with ML-specific tools like TensorFlow, PyTorch, Scikit-learn, etc.
• Scaling and Performance: Experience designing scalable AI systems, optimizing algorithms for high performance, and managing resource utilization effectively in large, distributed production environments.
• Strategic and Technical Leadership: Ability to define technical strategies, deliver hands-on engineering results, and work effectively within cross-functional teams. Experience in shaping product direction based on technical constraints and opportunities.
• Industry Experience: Experience in the cybersecurity, observability, or related domains is highly desirable, as understanding domain-specific challenges and user needs will be critical to success.

Splunk, a Cisco company, is an Equal Opportunity Employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, gender, sexual orientation, national origin, genetic information, age, disability, veteran status, or any other legally protected basis.

Note:

Thank you for your interest in Splunk!