Careers

Role Overview

We are looking for an AI Engineer to further automate our Atropos Health platform (Geneva OS) to revolutionize Real World Evidence (RWE). Our platform, already automated to some extent, generates rapid and reliable RWE and is prime for real-time clinical Q&A (ChatRWD) leveraging LLMs on our curated data sources.

You will work across Data Science, Product, Clinical and Engineering functions to shape AI project specifications and requirements to align with overall business goals. We are seeking innovative thinkers and builders who understand the state-of-the-art and can find opportunities to leverage them for our products. The ideal AI Engineer is one who embraces uncharted waters and has strong communications and engineering skills to propose and implement solutions to level up our platform.

Responsibilities

Stay abreast of research and conduct literature and empirical research to propose appropriate solutions (including non-AI ones) while sidestepping less promising ones. Advocate and drive the adoption of appropriate technologies.

Optimize existing generative AI models for improved performance scalability and efficiency

Propose appropriate LLMOps and frameworks (e.g. langchain) to make our models production-grade

Lead the development and fine-tuning of models with appropriate training data including the collection, annotation and management of training data

Articulate and deconstruct complex projects into workable solutions and identify appropriate data and methods. Manage and drive projects, working with stakeholders to address dependencies and gaps

Practice good judgment and solicit information to make good and timely design decisions

Test, productionalize and maintain products with software engineering best practices including code management and documentation

Requirements

Bachelors in Computer Science, Statistics or an equivalent discipline

At least 2 years’ professional experience as a AI/ML Engineer/Scientist or equivalent

You know when to use prompt engineering, RAG or fine-tune LLMs

Deep knowledge of AI frameworks (langchain, pytorch, tensorflow), prompt engineering with OpenAI and MLOps

Proficient in Python, Linux, git. cloud and big data infrastructure (e.g., AWS, GPUs, Docker, Spark, RDB, NoSQL, vector databases).

Experience conceptualizing, developing and productionalizing AI/ML applications

Experience manipulating and modeling large clinical datasets.

Flexible thinking: you know how to re-frame the problem to find practical solutions

Preferred

Deep knowledge of NLP especially NER

Familiarity with relevant medical coding terminology (e.g., ICD, CPT, LOINC, RxNORM) and handling Protected Health Information (PHI)

Excellent communication and written skills – you may be asked to contribute to our technical blogs and scientific publications

Excellent problem-solving, project management and team collaboration skills

Remote (US) - limited travel for company meetings.