Onsite
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.
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.
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)
Participate actively in client engagements, working directly with customers to understand requirements and deliver innovative solutions
Work closely with the rest of our team and CEO to make business decisions as we balance speed of growth and long-term profitability
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
Strong programming skills and general Computer Science knowledge
Strong 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 qualifications for this position. If you don't meet every single one of them, you should still consider applying! We’re excited to work with people from underrepresented backgrounds, and we encourage people from all backgrounds to apply.
Forus is based in New York, with our full team working out of a beautiful and spacious office in SoHo.
We run as a high-trust environment with high autonomy, which requires that everyone is fully competent and operates in line with our principles:
Do the math. Be rigorous, assume nothing. Break problems down and reason from the ground up.
Expand the solution space. Be resourceful and audacious. Resist false constraints and push beyond the obvious before committing.
Spit it out. Speak directly, invite critique, avoid equivocation. We want right answers, not comfortable ones.
Raise the bar together. Hold a high standard for execution, push each other directly, and win as a team.
We provide competitive compensation with meaningful equity (for full-time employees). Everyone who joins early will be a major contributor to our success, and we reflect this through ownership and pay.
We also provide rich benefits to ensure you can focus on creating impact (for full-time employees):
Fully covered medical, vision, and dental insurance.
Memberships for One Medical, Talkspace, Teladoc, and Kindbody.
Unlimited paid time off (PTO) and 16 weeks of parental leave.
401K plan setup, FSA option, commuter benefits, and DashPass.
Lunch at the office every day and Dinner at the office after 7 pm.
Our salary ranges are based on paying competitively for our company’s size and industry, and are one part of the total compensation package that also includes equity, benefits, and other opportunities at Forus (for full-time employees). Individual pay decisions are ultimately based on a number of factors, including qualifications for the role, experience level, skillset, geography, and balancing internal equity.
Forus is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law.
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