Staff Machine Learning Engineer

📋 Description

• • Nabla Bio is at the forefront of revolutionizing healthcare through advanced AI, and we are seeking an exceptional Staff Machine Learning Engineer to join our dynamic team in our Paris office. This pivotal role is designed for an experienced professional who will significantly influence the long-term direction and execution of our AI systems, driving innovation and ensuring the highest standards of quality and reliability. As a Staff ML Engineer, you will operate at a strategic level, collaborating closely with tech leads, product managers, and fellow engineers across multiple squads to embed cutting-edge machine learning capabilities into our leading AI assistant, Nabla. Our mission is to restore the human connection in healthcare by streamlining clinical documentation and workflows, allowing clinicians to dedicate more time to patient care. With over 85,000 clinicians and 130+ healthcare organizations already trusting Nabla, and backed by a recent $70M Series C funding, we are poised for significant growth and are looking for passionate individuals to help us build the next generation of clinical AI.
• • In this role, you will be instrumental in shaping Nabla’s agentic platform strategy, developing and executing the ML roadmap to enable increasingly configurable and autonomous workflows. This involves leading complex ML initiatives from conception through to production. Your responsibilities will span model design, sophisticated fine-tuning techniques, rigorous evaluation, and the critical aspects of context engineering for our AI agents. You will also be responsible for the seamless integration of these models into our production environment, ensuring their ongoing performance, reliability, and scalability.
• • A key aspect of your contribution will be driving our ML experimentation and evaluation frameworks. You will guide critical decisions regarding ML approaches, model selection, and tooling, ensuring that all choices are data-driven and focused on delivering measurable impact. This includes defining and owning comprehensive data strategies for both training and evaluation. You will ensure the highest standards of dataset quality, coverage, and versioning, and will be involved in data acquisition or annotation efforts when necessary to meet our ambitious goals.
• • Furthermore, you will play a crucial role in influencing our ML infrastructure and hardware decisions. Your expertise will be vital in ensuring that our training and inference workloads are not only scalable and reliable but also cost-efficient, allowing us to innovate rapidly without compromising on operational excellence. You will be a key voice in architectural discussions, ensuring our ML stack is robust and future-proof.
• • Beyond technical contributions, you will be a catalyst for raising the ML expertise across the organization. This will involve active mentorship of other engineers, conducting thorough design reviews, and staying abreast of the latest advancements in ML literature and technology. Your efforts will ensure that our ML initiatives remain tightly aligned with overarching product and business priorities, maximizing the value we deliver to clinicians and patients.
• • The ideal candidate possesses deep, hands-on experience with transformer-based models and Large Language Models (LLMs) in production environments. You should be adept at selecting the most appropriate ML techniques, whether it's prompt engineering, fine-tuning, retrieval-based approaches, or a strategic combination thereof, tailored to specific problem sets. Your background should include over 10 years of combined professional experience in machine learning and software engineering, with a proven track record of owning production systems throughout their entire lifecycle.
• • You will bring a strong blend of advanced ML expertise and solid software engineering principles, with a genuine commitment to building reliable, maintainable, and testable systems that can operate effectively at scale. A data-centric mindset is essential, coupled with practical experience in defining and implementing data strategies for ML model development and evaluation, covering aspects like quality, coverage, versioning, and acquisition/annotation workflows. Your comfort in making informed ML infrastructure decisions, including familiarity with cloud-based ML systems and hardware, will be key to optimizing performance, scalability, and cost.
• • We are looking for someone who can effectively balance ambition with pragmatism, enjoying the exploration of new ideas while remaining focused on delivering tangible, measurable impact. Your ability to influence technical direction through collaboration and mentorship, fostering a culture of shared learning and improvement, is highly valued. A strong product mindset, enabling you to connect ML decisions directly to user needs and business outcomes, is also a critical attribute for success in this role. Full professional fluency in both French and English is required, and experience beyond LLMs, such as classical ML or optimization techniques, would be considered a significant plus.