Xperi invents, develops and delivers technologies that enable extraordinary experiences. We make entertainment more entertaining, and smart devices smarter.
From the home to the car to everywhere in between, managing content and connections in a way that is smart, immersive, and personal is precisely what Xperi’s technologies do.
Our inventions are foundational to the global entertainment ecosystem and our products and data improve every aspect of the digital entertainment experience, from choice to consumption.
Content markets are changing, fast. Consumers face a simultaneously expanding and fragmenting set of choices. Xperi technology cuts through the chaos, putting us at the forefront of fast-moving trends in streaming, digital entertainment, and AI applications – in any environment.
Xperi is at the heart of extraordinary experiences.
We can’t wait to show you what’s next. TiVo is seeking an Applied LLM Engineer to join our Personalized Content Discovery Data Science team. This position focuses on building and integrating large language model (LLM)-based solutions into internal tools and customer-facing applications. The role involves, experimenting with and prototyping generative AI model applications, designing robust prompts, managing prompts, and integrating with LLM services via APIs. Our data science team works on research and development for several TiVo products:Search and Recommendation (Video/Music Content Recommendation System),Insight (Data Analytics)Conversation (Voice Entertainment Assistant)Video and Music Metadata (Textual, Image, Quantitative) On our team you can expect to work with a variety of data sources and customer solutions across the entertainment and product engineering domain. Our mission is to help our customers find, watch, and enjoy their favorite content. ResponsibilitiesDesign, test, and refine prompts for LLM-based applicationsConduct data analysis and model evaluation to track performance across use casesIntegrate LLM and GenAI APIs (e.g., OpenAI, AWS) into internal productsDevelop lightweight backend services (e.g., FastAPI) to prototype model usageDocument systems and experiments clearly Preferred ExperienceFamiliarity with basic data engineering tools with emphasis on pysparkKnowledge of vector search and retrieval techniquesSolid data science and statistical backgroundRequirementsM.S. degree in Computer Science, Data Science, Engineering, or a related technical field or equivalent hands-on experience in AI/ML engineeringExperience with LLM APIs, prompt engineering, and experimentationFamiliarity with AWS cloud servicesComfort working with API integration and multi-modal data (text, JSON, metadata)Ability to run and evaluate open-source models both locally and in the cloudStrong communication and presentation skills to share findings across teams
Life @ Xperi: At Xperi, we value People, Customers, Performance and Innovation. We are dedicated to creating a workplace where all employees have a voice and sense of belonging, feel safe and valued, and are acknowledged for how their unique differences contribute to organizational culture and business outcomes. Our employees and their families are important to us, and our comprehensive pay, stock and benefits programs reflect that. Xperi supports personal well-being, builds financial security and enables employees to share in our collective success. Rewards include: Competitive compensation (salary, equity and bonuses) and comprehensive benefits designed to foster work-life balance, care for your health, protect your finances and help you save and invest for the future. Generous paid time away from work, including flexible time off, holidays and sick time, health and wellness initiatives, and a charitable match program to help you give back to your community. Great perks, which vary by location and can be site-specific: employee discounts, transportation reimbursements, subsidized cafes and fitness facilities. A flexible, hybrid work environment combining the best of in-office collaboration and community-building along with the benefits of working from home.