Research Engineer

Forus Inc

$100K — $150K *
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Strong programming skills and general Computer Science knowledge
  • Research background in ML/NLP with publications in top-tier conferences or significant open-source contributions
  • Experience on complex ML problems and deploying solutions in production environments
  • Deep understanding of modern ML methods such as transformer architectures and reinforcement learning
  • Proficiency in deep learning frameworks like PyTorch, TensorFlow, or JAX
  • Excellent written and verbal communication skills
  • Proven track record of efficiency and problem-solving in achieving goals

Responsibilities

  • Scope and lead AI augmentation and automation projects across product areas
  • Stay updated on emerging AI methods to guide model selection
  • Establish and execute research strategies for AI methods
  • Develop novel algorithms for NLP and autonomous reasoning
  • Automate complex workflows for insurance processes
  • Enhance data and ML pipeline robustness against input variations
  • Translate heterogeneous data into actionable insights for biopharma partners

Benefits

  • 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 setup, FSA options, commuter benefits, and DashPass
  • Daily lunch and dinner provided for late office hours
Full Job Description


All full-time roles are in person in New York.

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're looking for you 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 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.

Working with us

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 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.

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