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Parallel
Paris, Ile-de-France, France • On-site
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Design and deploy production-ready LLM and agent-based systems to automate medical coding and administrative workflows. Partner with the CTO to define the AI roadmap and own the full lifecycle of AI features from research to monitoring.
Requires 3+ years of experience in applied ML/AI in production environments with strong proficiency in Python or Node.js. Candidates must have experience with LLMs, NLP, and building scalable data pipelines.
Today, up to 25% of healthcare spending is lost in manual, repetitive administrative work. Legacy software hasn’t helped, it’s made things slower, more complex, and more frustrating for care teams.
We believe AI agents can change that. Our technology combines Large Language Models with system-level automation to handle real work inside existing hospital tools. No integrations, no disruption.
Our first agent automates coding workflows and frees up time for medical staff to focus on patients.
We launched in 2024, are backed by top investors (Index, Frst, Y Combinator, Hexa, Kima Ventures, Better Angle), and we’re just getting started.
The future of healthcare isn’t just digital — it’s automated. Come help us build it !
Up to 25% of healthcare spending is lost in manual, repetitive administrative work — and the AI systems that can fix it only matter if they actually run in production, inside real hospitals, on sensitive health data. Building that is the heart of this role.
This is a founding AI Engineer role: you won't just write models, you'll shape Parallel's core AI architecture, define our machine learning strategy, and embed intelligent systems directly into hospital workflows. You'll work hand in hand with the CTO and the founding team, with very high ownership over everything from agentic LLM workflows to the way AI outputs land in the tools doctors actually use.
Design and deploy production-ready AI systems — LLM-powered and agent-based — that automate medical coding and reduce administrative workload in hospitals, owning each feature from prototype to monitoring.
Production LLM systems: design and deploy LLM-powered systems that automate medical coding in real clinical environments.
Agentic workflows: build and iterate on agent-based workflows tailored to complex clinical operations.
Secure data pipelines: work with hospital IT to build secure, scalable data ingestion pipelines that adhere to health-data security standards.
Product integration: integrate AI outputs into the apps used by doctors and hospital staff.
AI roadmap & full ownership: partner with the CTO to define the AI roadmap, and own the full lifecycle of each AI feature — research, prototyping, evaluation, deployment, and monitoring.
You have 3+ years working on applied ML/AI problems in production environments — real systems that run, not just POCs.
You have strong experience with LLMs and NLP, including prompt engineering and/or fine-tuning.
You're proficient in Python or Node.js and have worked with ML libraries (Hugging Face, LangChain, PyTorch, etc.).
You have a deep sense of ownership and can move from prototype to product quickly.
You're action-oriented and autonomous, and you thrive in a fast-paced startup where you shape the core, not execute tickets.
You care about solving user problems over shipping features, and you're comfortable getting close to the product and its users.
Bonus: familiarity with backend services (Node.js/TypeScript) and data infrastructure.
Bonus: experience working with sensitive or regulated data (healthcare, finance, etc.).
Quick chat with Wallerand, our recruiter (30 min)
Chat with our CTO, Chris (30 min)
AI / technical case study, in person at our Paris office (60 min)
Meeting with our CEO, Paul (30 min)
A rare founding opportunity: you shape Parallel's core AI architecture and ML strategy from day one, with very high ownership alongside the founders.
Real-world impact: your systems directly reduce hospital burnout and free up medical staff to focus on patients, not paperwork.
Cutting-edge work that ships: state-of-the-art LLM and agentic systems deployed into real clinical environments — with the engineering rigor (type safety end to end, automated best practices, rapid iteration with tools like Cursor) to make them reliable.
Package & perks: competitive salary and meaningful equity, plus our standard benefits (Alan health insurance, Swile meal vouchers, Apple equipment, 50% public-transport coverage).
On-site in Paris, 100% in person — building something this ambitious works best shoulder to shoulder.
We care about who you are, not just what's on your CV.
If you're drawn to what we're building but don't meet every requirement, we still want to hear from you. Studies show that women in particular tend to apply only when they meet 100% of the criteria. If that's you, please don't let that hold you back. We'd love to receive your application.
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