Principal Machine Learning Engineer
Description
Responsibilities
- Develop Core AI Engineering Capabilities: Design and implement AI/ML models and orchestration that drive critical use cases across Splunk’s product offerings.
- Build Production-Ready AI Agents: Design, implement, and fine-tune conversational AI solutions, including chatbots and virtual assistants, using natural language processing (NLP), dialogue management systems, and large language models (LLMs).
- Research and Innovation: Stay at the forefront of AI/ML developments, incorporating pioneering research into practical, applied solutions. Investigate and integrate new methodologies, such as advancements in Gen AI and LLMs, into our product ecosystem.
- Collaborate Across Teams: Partner with diverse 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.
- 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
- 9+ years of total professional experience, including a minimum of 5 years in the machine learning domain.
- 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.
- Generative AI and LLM Expertise: Significant experience working with generative AI models, large language models (LLMs), and integrating them into enterprise-level applications.
- Conversational AI Expertise: Proven experience in building and deploying conversational AI systems, including NLP, intent recognition, and dialogue management. Expertise in designing RAG pipelines and implementing guardrails to ensure robust, secure, and ethical chatbot interactions.
- Coding and Algorithm Development: Proficiency in modern programming languages such as Python. Strong skills and experience with ML-specific tools like TensorFlow, PyTorch, Scikit-learn, etc.
Note:
Base Pay Range
India
Base Pay: INR 4,800,000.00 - 6,600,000.00 per year
Splunk provides flexibility and choice in the working arrangement for most roles, including remote and/or in-office roles. We have a market-based pay structure which varies by location. Please note that the base pay range is a guideline and for candidates who receive an offer, the base pay will vary based on factors such as work location as set out above, as well as the knowledge, skills and experience of the candidate. In addition to base pay, this role is eligible for incentive compensation and may be eligible for equity or long-term cash awards.
Benefits are an important part of Splunk's Total Rewards package. This role is eligible for a comprehensive, competitive benefits package which may include healthcare and retirement plans, paid time off, wellbeing expense reimbursement, and much more! Learn more about our next-level benefits at https://splunkbenefits.com.
Thank you for your interest in Splunk!