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The proliferation of machine log data has the potential to give organizations unprecedented real-time visibility into their infrastructure and operations. With this opportunity comes tremendous technical challenges around ingesting, managing, and understanding high-volume streams of heterogeneous data
As a Machine Learning Engineer, you'll be the driving force behind creating the magic that powers the next generation of AI tools. In this groundbreaking role, you’ll help develop and refine prompt engineering techniques, constantly exploring innovative ways to improve generative AI.
Responsibilities- Design and create prompts that guide large language models to produce specific, accurate, and exceptional responses.
- Craft precise and creative prompts that guide AI toward desired outcomes, fine-tuning the results for accuracy and excellence.
- Collaborate with Product Leads, Data Engineers, Developers, and other creative minds to translate needs into effective prompts, enhancing the impact of AI solutions.
- Test and evaluate the effectiveness of both existing and newly developed prompts. - Develop and maintain a comprehensive library of prompts, ensuring clarity, effectiveness, and best practice sharing. Experience with Prompt evaluation is also critical to this role.
- Work with cross-functional teams to integrate prompt engineering models into production environments.
- Work as a member of a team, helping the team respond quickly and effectively to business needs.
- B.Tech, M.Tech, or Ph.D. in Computer Science or related discipline
- 5+ years of industry experience with a proven track record of ownership and delivery
- 5+ years of experience working cross-functionally with both technical and non-technical teams
- Solid grounding in core ML concepts and basic statistics
- Languages: expert level with Python, familiarity with JVM languages is a plus
- LLM core concepts, libraries, and application design patterns
- Experience defining program requirements and using data to drive improvements
- Common ML libraries (eg, scikit-learn, PyTorch) and components (eg, Airflow, MLFlow)
- Relevant cloud provider services (eg, AWS Sagemaker)
- Agile software development experience (test-driven development, iterative and incremental development) is a plus.
- LLM Ops experience - Infrastructure, Performance & Observability
Sumo Logic, Inc. empowers the people who power modern, digital business. Sumo Logic enables customers to deliver reliable and secure cloud-native applications through its Sumo Logic SaaS Analytics Log Platform, which helps practitioners and developers ensure application reliability, secure and protect against modern security threats, and gain insights into their cloud infrastructures. Customers worldwide rely on Sumo Logic to get powerful real-time analytics and insights across observability and security solutions for their cloud-native applications. For more information, visit www.sumologic.com.
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