Owkin

<h2>About us</h2>Owkin is an agentic AI company pioneering Biological Artificial Superintelligence to solve problems in biology where human researchers alone have failed. Owkin builds K Pro - an AI scientist for pharmaceutical research and strategic decision-making. K Pro orchestrates a suite of AI skills and tools to decode complex biology, accelerate research, and dramatically increase productivity. K Pro is built on Owkin’s unrivalled multimodal patient data network, state-of-the-art AI for biology and a decade of experience working with pharmaceutical partners.Position is based in our Paris offices or remotely in France, UK, or Germany.Please submit your CV in English<h2>About the role:</h2>We are seeking a highly skilled and experienced Scientist II Machine Learning Engineer to design, develop, and deploy cutting-edge AI solutions. In this role, you will focus heavily on Large Language Models (LLMs), Generative AI, and Advanced Deep Learning architectures. You will bridge the gap between experimental data science and production-ready ML systems. Working closely with our Data Science and Engineering teams, you will scale complex models, optimize training and inference pipelines, and leverage cloud ecosystems to deliver robust biomedical solutions. Experience handling health, clinical, or omics data (genomics, transcriptomics, proteomics, etc.) is a major plus. <h2>In particular, you will:</h2><ul><li>Develop scalable machine learning libraries, tooling, and research workflows in close partnership with research and data scientists.</li><li>Shape research infrastructure requirements and drive tool and software choices in collaboration with the platform team.</li><li>Champion software engineering best practices across the team, enabling researchers and scientists to write maintainable, testable, efficient, and scalable code.</li><li>Design and enhance systems for experiment tracking, reproducibility, and end-to-end model lifecycle management.</li><li>Contribute to and accelerate the rapid prototyping of novel models, helping bridge early research and robust implementation.</li><li>Other Ad-hoc responsibilities, tasks and projects assigned by the management.</li></ul>  <h2>About you</h2>Required qualifications / experience:<ul><li>Education: Master’s or Ph.D. in Computer Science, Data Science, or a related quantitative field with a strong focus on ML/AI.</li><li>Experience: 5+ years of professional experience in software development with Python and a proven track record of deploying deep learning models into production.</li><li>ML/DL Frameworks &amp; Ecosystems: Deep understanding of machine learning algorithms, statistical methods, and deep learning frameworks. Mastery of PyTorch or TensorFlow.</li><li>LLM Specialization: Deep understanding of Transformer architectures, attention mechanisms, and the latest breakthroughs in Generative AI. Extensive experience with Hugging Face, with knowledge in agentic workflows and RAG.</li><li>Cloud &amp; MLOps: Experience with cloud platforms (AWS, GCP, or Azure) and SageMaker</li><li>Software Engineering Culture: Strong engineering practices including version control, comprehensive testing, CI/CD, and containerization (Docker).</li><li>Workflow Optimization: Experience with distributed computing, distributed training strategies for massive datasets, and optimization of ML workflows (e.g., vLLM).</li></ul>Preferred qualifications/bonus:<ul><li>Domain Expertise: Experience working with clinical or omics data (e.g., genomic sequencing, transcriptomics, electronic health records) and medical imaging processing and analysis.</li><li>Contributions to open-source ML projects or research publications.</li></ul>Soft skills and culture add:<ul><li>Collaborative Mindset: Excellent problem-solving skills and the ability to analyze complex technical challenges. </li><li>Strong communication skills: The ability to explain technical concepts to various stakeholders.</li><li>Mentorship: Proactive approach to debugging complex distributed systems, mentoring team members in writing high-quality, maintainable software, and driving a strong technical culture.</li><li>Autonomy: primarily autonomous and capable of being given tasks without excessive detail, able to figure out what to do and execute.</li></ul>#LI-HB1 <h2>What we offer</h2><ul><li>Flexible work organization</li><li>Friendly and informal working environment</li><li>Opportunity to work with an international team with high technical and scientific backgrounds</li></ul><h2>Recruitment Process &amp; Security</h2><ul><li>Please complete the form and submit your CV.</li><li>Owkin is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, sex, gender, sexual orientation, age, color, religion, national origin, protected veteran status or on the basis of disability.</li><li>Owkin is a great place to work. As a coveted workplace we are, unfortunately, vulnerable to recruitment phishing scams. We urge all job seekers and candidates to be wary of potential scams. Most of these have individuals posing as representatives of prominent companies, including Owkin, with the aim of obtaining personal, sensitive, or financial information from applicants. These scams prey upon an individual’s desire to obtain a job and can sometimes “feel” like a genuine recruitment process. Some red flags are identified below. Should you encounter a recruitment process that claims to be for Owkin but is not consistent with the below, please do not provide any personal or financial information:</li><li>Legitimate Owkin recruitment processes include communication with candidates through recognized professional networks, such as LinkedIn.</li><li>Communication is always through an official Owkin email address (from the @<a target="_blank" rel="noopener noreferrer ugc" href="http://owkin.com">owkin.com</a> domain), over the phone or through our applicant tracking system (Greenhouse).</li><li>The Owkin talent team do use platforms such as LinkedIn and Job Teaser, however if you have any concern or doubt about this contact, please ask for them to send an email from @<a target="_blank" rel="noopener noreferrer ugc" href="http://Owkin.com">Owkin.com</a>.</li><li>The Owkin talent team will not solicit personal data from candidates during the application phase including, but not limited to, date of birth, social security numbers, or bank account information;</li><li>Legitimate Owkin interviews may be conducted over the phone, in person, or via an approved enterprise videoconferencing service (Google Meets). They will not occur via Signal, Telegram or Messenger</li><li>Owkin offers of employment are based on merit and only extended once a candidate has interviewed with members of the talent and hiring team. Offers will be extended both verbally and in written format.</li></ul>If you think that you have been a victim of fraud,<ul><li>Check the identity of the talent team on LinkedIn</li><li>Check our senior team on our website <a target="_blank" rel="noopener noreferrer ugc" href="https://owkin.com/team/">https://owkin.com/team/</a></li><li>Check the existence of the position on our website: <a target="_blank" rel="noopener noreferrer ugc" href="https://www.owkin.com/careers#current-opportunities">https://www.owkin.com/careers#current-opportunities</a></li><li>Notify Owkin's recruitment unit at this address <a target="_blank" rel="noopener noreferrer nofollow" href="mailto:hiring@owkin.com">hiring@owkin.com</a></li><li>contact the following authorities:<ul><li>[FR] <a target="_blank" rel="noopener noreferrer ugc" href="https://internet-signalement.gouv.fr/">https://internet-signalement.gouv.fr/</a></li><li>[UK] <a target="_blank" rel="noopener noreferrer ugc" href="https://www.actionfraud.police.uk/reporting-fraud-and-cyber-crime">https://www.actionfraud.police.uk/reporting-fraud-and-cyber-crime</a></li><li>[US] <a target="_blank" rel="noopener noreferrer ugc" href="https://reportfraud.ftc.gov/">https://reportfraud.ftc.gov/</a></li></ul></li></ul>

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Scientist II Machine Learning Engineer (LLM & GenAI Specialist)

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