Applied AI software engineer

• Design & Prototype (40%): Collaborate with product managers and designers to design and prototype AI-powered features targeting oncologist workflows and real world evidence research. Experiment with LLMs, NLP models, and ML frameworks to validate concepts before full development.
• Build & Integrate (40%): Develop production-ready features using Python and modern ML/NLP frameworks. Work with Product Engineering Teams to seamlessly integrate AI capabilities into existing products, ensuring quality through CI/CD pipelines and automated testing.
• Maintain & Optimize (20%): Monitor deployed features for reliability and performance. Collaborate with the Data Reliability Engineering Team to leverage curated healthcare data, and document systems for knowledge sharing., This team is in its early stages. Alongside Ivan, your manager and ML engineer, you will form the core of it. The team's goal is to accelerate the delivery of AI features within our products-whether by using off-the-shelf AI tools, developing models for well-identified needs, or integrating models built by ML researchers in other teams. You'll work closely with Noémie and Anthony (Product & Delivery Team).

Do you have experience in Python?, * Develop Python products with 3+ years of experience

• Work with ML/NLP/LLM frameworks and libraries
• Use version control systems and CI/CD tools
• Deliver products using Docker, APIs, and service architecture
• Communicate fluently in English and at least B2 level in French (main language used in the company and the daily language), * Autonomous: You work effectively even when goals are unclear or evolving
• Analytical: You turn ideas and intuitions into concrete, actionable solutions
• Proactive: You identify problems and propose solutions
• Open communicator: You share your thinking, ask questions, and collaborate transparently
• Versatile: You adapt to different types of problems requiring varied skills (AI, ops, architecture…), * Built and deployed ML/NLP features in production environments
• Collaborated with product teams to translate user needs into technical solutions
• Worked in ambiguous environments where you had to balance multiple technical challenges, * Have extensive NLP experience beyond basic applications
• Have in-depth knowledge of LLMs (fine-tuning, prompting, RAG, etc.)
• Have experience with healthcare data and clinical workflows
• Have a background in oncology or life sciences domains

You'll be at the forefront of our innovation strategy, directly impacting patient care and real-world evidence research. By prototyping and delivering production-ready AI features, you'll help us achieve our vision of empowering oncologists with cutting-edge technology.