About the role
Profound is on a mission to help companies understand and control their AI presence. As an AI and ML Engineer, you will design, build, and ship large scale NLP and LLM systems that power classification, ranking, clustering, topic discovery, and content generation. You will own workflows from data to deployment, partner across product and engineering, and turn real user conversations into production features and publish-ready content that drives visibility, engagement, and conversion. What you’ll do Build and deploy NLP models at scale for classification, ranking, clustering, topic extraction, and summarization Design LLM workflows for context and content generation end to end, including topic discovery, brief creation, outlines and drafts, revision loops, and publish-ready assets Develop prompt and template libraries aligned to brand voice and channel, including blogs, landing pages, help docs, and ads, with retrieval for evidence-grounded generation and citations Create evaluation frameworks for generated content, including factuality, coverage, tone, safety, and originality, with rubric-based LLM evaluations, human-in-the-loop review, and red teaming Instrument content performance across AEO and SEO visibility, engagement, and conversion, and run experiments to improve quality, cost, and latency Transform large text datasets into production features and signals that drive product insights Partner with engineering to instrument events, maintain data pipelines, and uphold high data quality and observability Collaborate with product, data, and go-to-market teams on success metrics and experiments that move customer-facing KPIs
Who you are Proven experience shipping machine learning systems in production at scale, especially with large text data Hands-on experience building LLM content systems including prompting, templating, retrieval or RAG, guardrails, and evaluations Fluency in SQL and strong Python skills with modern machine learning tooling Strong grasp of machine learning and generation quality metrics, with the ability to design offline and online evaluations and monitoring Ability to innovate when off-the-shelf solutions do not fit the problem Experience working in cross-functional, high-performance teams Clear communication with both technical and non-technical partners Ownership mindset and comfort operating in a fast-paced environment Excited by ownership of the entire product analytics function at an early stage company Motivated by shaping how usage is measured and how product decisions are made Interested in close collaboration with product, engineering, and go-to-market teams Comfortable in a fast-paced environment with trust, autonomy, and responsibility Drawn to competitive