Research Scientist

About Engram EngramToday’s AI is designed to solve complex problems by learning your context and preserving it in compact, parametric memories. We work with leading AI companies and have received funding from major venture capital firms. About this role As a Research Scientist you will join a small, focused team of researchers and engineers at the frontier of learning and memory. You will design experiments, develop new recipes, build evaluations, and shape the product used by some of the world's leading tech and AI companies. Responsibilities Design and evaluate methods for encoding large, heterogeneous document corpora into compact parametric memory (e.g., LoRA/adapter-based representations, prefix tuning, state‑space methods). Investigate synthetic training data generalization and develop self‑study pipelines that allow models to reflect on and consolidate new context. Address catastrophic forgetting, sequential updates, knowledge conflicts, and tradeoffs between in‑weights memory and agentic retrieval in continual learning algorithms. Explore reinforcement learning methods that enable models to improve from interaction and feedback in real deployment settings. Empirically study how model capacity, data scale, and compute interact; develop scaling laws that inform the product roadmap. Qualifications Deep background in machine learning with strong fundamentals in inference serving systems, KV cache design, or latency‑sensitive model deployment. Track record of rigorous ML research – publications, strong open‑source contributions, or equivalent demonstrated depth. Extensive experience in at least one area directly relevant to our work: continual learning, memory architectures, test‑time training, parameter‑efficient finetuning, context compression, retrieval, synthetic data, distillation, or agents. Comfortable working up and down the stack – understanding research questions and the systems that run them, not just writing papers. Strong technical communication skills – ability to simplify complex ideas and engage in detailed technical conversation. Bonus: Experience bridging research and product – shipping things that real users interact with. Familiarity with LLM training infrastructure. Location & Compensation Engram is based in San Francisco. This role is in‑person in our SF office. We offer competitive cash compensation and startup equity. Equal Opportunity Engram is an equal‑opportunity employer. We’re building a team that reflects a range of backgrounds and perspectives, and we welcome applicants regardless of race, color, religion, national origin, gender, gender identity, sexual orientation, age, disability, or veteran status. #J-18808-Ljbffr Engram