Machine Learning Engineer, Applied Research and Model Development at Lightfield

About LightfieldLightfield is a new kind of CRM.It's a collaborative system for founders to find, understand, and serve customers faster than anything before it.It captures every customer interaction, generates and performs followup actions, and answers questions about your go-to-market using knowledge obtained in real time.Our system is tuned and customized by a team of experienced sellers, engineers, and researchers. Many of us worked on large-scale products including Llama, Messenger, Instagram, Pinterest, and Linkedin before this.Lightfield.appAbout the roleLightfield's AI/ML team builds the experiences at the core of our product, developing new applications to wow our customers.Today, the team is focused on building a powerful, domain-specific AI that outperforms generic LLMsWe’re inspired by the challenge of creating innovative new AI products for people doing serious work, and we’re looking to grow our AI/ML team to meet that challenge.What you'll doCreate and ship magical, highly-differentiated AI experiences that sales teams can’t live withoutCraft Lightfield AI/ML strategy in tight collaboration with founders and execsPioneer the training of new models that leverage both historical data and synthetic training dataPrototype innovative, LLM-powered experiences, and drive their development into robust product featuresHelp build a world class AI/ML engineering team by recruiting and mentoring teammatesWho you areYou have 5+ years of industry experience in NLP, with a strong portfolio of model trainingYou have a strong understanding of deep learning AI/ML frameworks or cloud servicesYou have hands-on ML Ops experienceYou possess deep expertise in NLP and model training, specifically with LLMsProven experience adapting open-source generative models for specific use cases, demonstrating a deep understanding of its architecture and capabilitiesBonus PointsProven track record of leading successful AI/ML research projects in a product environmentPublications in applied AI/ML scientific journalsExperience navigating open source/vendor solutions in LLM ops space (Langchain, Llama, Pinecone, etc)