About the role
Why you should join us Forus is a generational opportunity to rethink how we bring new therapies to market, and our path to doing so is significantly de-risked – we have: Exponential organic growth: We have product-market fit and are growing rapidly. Forus supports thousands of new patients every day, is spreading with doctors through word-of-mouth, and works with the largest biopharma companies in the world. An AI-first business model: Our approach is distinctly enabled by AI, but our business gets stronger (not commoditized) as foundation models improve. We are building durability through two-sided network effects that compound over time. Top tier investors: With the traction to support conviction in our model, we raised significant funding from top investors (Thrive Capital, General Catalyst, and Accel) to build an exceptional team of engineers and operators. Our number one priority is scaling to market demand . We are looking for individuals who are high horsepower, high throughput, and hyper resourceful to help us increase capacity and grow. We move fast and need to move faster. All full-time roles are in person in New York. You can learn more about working with us in the last section of this page.
About
the role As a Research Engineer on our team, you will work on real production use cases of LLMs and other ML techniques to solve business problems and create groundbreaking AI applications.
The role requires that you develop a deep understanding of our product surface area and what drives our business, such that you can operate and drive impact both cross-functionally and independently. You will have end-to-end responsibility for projects, including definition, design, development, launch, and success––this includes ensuring your output has the expected impact on user growth, operational efficiency, or revenue generation. This is a demanding role, with a high level of autonomy and responsibility. You will be expected to "act like an owner" and commit yourself to Forus' success. If you are low-ego, hungry to learn, and excited about intense, impactful work that drives both company growth and accelerated career progression, we want to hear from you. If you join, you will: Scope and spearhead AI augmentation and automation projects across our product surface area, including: Unintuitive classifications, Data extraction and summarization, Precise content generation, Reference-based search and question answering, Process outcome prediction, Probabilistic triggering of workflows, and Multimodal LLM-powered bots Stay on top of emerging AI methods and guide decisions around which models and techniques to adopt––including evaluating when to use open-source models, proprietary models, and custom fine-tuning approaches Establish research strategies for various AI methods, including rigorous experimentation and evaluation protocols that account for accuracy, consistency, interpretability, and real-world impact Develop novel algorithms and techniques to address core research problems in natural language processing, data extraction, and autonomous reasoning (e.g., few-shot learning, agentic reasoning, and multi-modal interaction) We need your help to: Decipher and automate complex, branching workflows for insurance coverage, affordability programs, and fulfillment Combining AI/ML approaches to achieve high precision document classification, unstructured data extraction, and reference-based question answering Automating multi-step, path-dependent processes, using a combination of RPA/scraping approaches to navigate and operate third-party platforms Building a state machine that drives system decisions and handles failure modes across a set of processes that are technically independent but practically intertwined Scale across a growing range of drug classes, patient populations, and provider markets Making our data and ML pipelines robust to variation and inconsistency in input data formats (e.g., clinical documentation structure and style) Leveraging empirical data to build and continuously update our understanding of opaque external systems (e.g., insurance company policies) Creating consumer-grade experiences for patients, physicians, and other users that incorporate intuitive AI-powered workflows Use our network to help biopharma partners accelerate drug development, launch, and access Translating large volumes of heterogeneous data into reliable insights, informing decisions like clinical indication selection, launch markets, and insurer negotiations Developing predictive and simulation models to forecast outcomes such as clinical trial site performance, drug adoption rates, and the impact of rebates/subsidies Using real-time data and direct engagement channels to enroll criteria-matching patients and physicians in clinical studies and access programs We’ll be most excited if you have: Strong programming skills and general Computer Science knowledge Research background in ML/NLP, demonstrated through publications in top-tier conferences (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP) or significant open-source contributions Experience working on complex ML problems (e.g., data-efficient learning, reasoning agents, or multi-step workflows) and deploying those solutions in production environments Deep understanding of modern ML methods, including transformer architectures, attention mechanisms, reinforcement learning, and multimodal models — with proficiency in deep learning frameworks such as PyTorch, TensorFlow, or JAX Strong written and verbal communication that allows you to be an effective participant in both internal debates and external relationships Track record of moving quickly, finding shortcuts, and going to unreasonable lengths to deliver on goals High NPS with your former teammates This is a list of ideal
