This list contains only the countries for which job offers have been published in the selected language (e.g., in the French version, only job offers written in French are displayed, and in the English version, only those in English).
You will join our global Machine Learning and Data Science unit — a core team of machine learning scientists (LLM, ASR), engineers and an expanding group of country-specific linguists. Your work will be embedded in the ever-growing Noa product line used daily by doctors in Brazil, Mexico, Poland, Italy, Spain and Germany. Noa.ai’s mission is to broaden access to top-quality healthcare, first by lifting administrative burdens from clinicians and soon, by assuming selected medical tasks. Our flagship product is Noa Notes, which records consultations, transcribes the audio and produces a structured draft of the medical record. We operate cross-functionally, moving ideas from prototypes to full-scale production with state-of-the-art ML frameworks and modern MLOps practices. We begin with rapid validation sprints where engineers work side by side with Product on early experiments, then consolidate and scale proven capabilities, standardizing validation methods, engineering best practices, tools and lifecycles.
Job Responsibility:
Work closely with cross-functional teams, including scientists, engineers, and product stakeholders, to deliver LLM-driven initiatives that directly contribute to business objectives
Design, deploy and iterate over LLM services for text-based applications (and beyond), while proactively identifying and eliminating performance bottlenecks
Build small to medium-sized Python projects and collaborate with engineers on production code and deployments at scale
Assess platform engineering and LLMOps bottlenecks
research and design scalable prompt management strategies, and recommend solutions that balance performance, cost, and reliability
Research, architect, and deploy LLM-powered information retrieval solutions (e.g., RAG) to deliver accurate results in complex, multilingual product environments
Partner with the AI Platform team to refine LLMOps best practices, evolve frameworks, and establish efficient, scalable workflows
Requirements:
At least one year of professional experience in LLM development or integration in a fast-paced, product-driven tech environment
Demonstrated expertise in production-grade LLM deployments, including prompt management systems, vector databases, semantic search implementation, and API integration with foundation models
Good understanding of transformer architectures and proficiency in LLM frameworks such as LangChain, LlamaIndex, or similar tools
Proficiency in Python
Experience in collaborative project development
Appreciation for good engineering practices and maintainable code
Proven experience in evaluating LLMs through systematic testing, benchmark design, and the development of custom metrics (e.g. accuracy, consistency, factuality, and bias), with a focus on aligning results to product and user needs
Proven ability to integrate, deploy, and optimize large language models in production-grade industry environments, ensuring scalability and robust performance
Strong knowledge in prompt engineering, agent-based workflows, and the generation and manipulation of embeddings
Experience with RAG (Retrieval-Augmented Generation) techniques, vector similarity search, and information retrieval methods to enhance LLM capabilities
Problem-solving mindset and adaptability in dynamic environments with a focus on delivering business value to end customers
Proven ability to manage timelines, prioritize tasks, and deliver results under tight deadlines
Curiosity and eagerness to collaborate with cross-functional team
What we offer:
Flexible remuneration and benefits system via Flexoh, which includes: restaurant card, transportation card, kindergarten, and training tax savings
Share options plan after 6 months of working with us
Remote or hybrid work model with our hub in Barcelona
Flexible working hours (fully flexible, as in most cases you only have to be on a couple of meetings weekly)
Summer intensive schedule during July and August (work 7 hours, finish earlier)
23 paid holidays, with exchangeable local bank holidays
Additional paid holiday on your birthday or work anniversary (you choose what you want to celebrate)
Private healthcare plan with Adeslas for you and subsidized for your family (medical and dental)
Access to hundreds of gyms for a symbolic fee in partnership for you and your family with Wellhub
Access to iFeel, a technological platform for mental wellness offering online psychological support and counseling
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