---
title: 'Scientist II Machine Learning Engineer (LLM & GenAI Specialist) at Owkin'
canonical: 'https://feeny.ai/job/scientist-ii-machine-learning-engineer-llm-genai-specialist-owkin-paris-e9jfkvz7q40q'
type: 'job'
last_seen: '2026-10-18'
---

# Scientist II Machine Learning Engineer (LLM & GenAI Specialist) at Owkin

- **Company:** Owkin
- **Location:** Paris, France
- **Employment:** full-time
- **Work type:** hybrid
- **Posted:** 2026-07-15
- **Last confirmed live:** 2026-10-18
- **Apply:** https://jobs.ashbyhq.com/owkin/df08e875-432e-420f-ac18-543c07e0ee1b

## Job description

## About us

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

About the role: 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.

In particular, you will:

- Develop scalable machine learning libraries, tooling, and research workflows in close partnership with research and data scientists.
- Shape research infrastructure requirements and drive tool and software choices in collaboration with the platform team.
- Champion software engineering best practices across the team, enabling researchers and scientists to write maintainable, testable, efficient, and scalable code.
- Design and enhance systems for experiment tracking, reproducibility, and end-to-end model lifecycle management.
- Contribute to and accelerate the rapid prototyping of novel models, helping bridge early research and robust implementation.
- Other Ad-hoc responsibilities, tasks and projects assigned by the management.

## About you

Required qualifications / experience:

- Education: Master’s or Ph.D. in Computer Science, Data Science, or a related quantitative field with a strong focus on ML/AI.
- Experience: 5+ years of professional experience in software development with Python and a proven track record of deploying deep learning models into production.
- ML/DL Frameworks & Ecosystems: Deep understanding of machine learning algorithms, statistical methods, and deep learning frameworks. Mastery of PyTorch or TensorFlow.
- 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.
- Cloud & MLOps: Experience with cloud platforms (AWS, GCP, or Azure) and SageMaker
- Software Engineering Culture: Strong engineering practices including version control, comprehensive testing, CI/CD, and containerization (Docker).
- Workflow Optimization: Experience with distributed computing, distributed training strategies for massive datasets, and optimization of ML workflows (e.g., vLLM).

Preferred qualifications/bonus:

- Domain Expertise: Experience working with clinical or omics data (e.g., genomic sequencing, transcriptomics, electronic health records) and medical imaging processing and analysis.
- Contributions to open-source ML projects or research publications.

Soft skills and culture add:

- Collaborative Mindset: Excellent problem-solving skills and the ability to analyze complex technical challenges.
- Strong communication skills: The ability to explain technical concepts to various stakeholders.
- Mentorship: Proactive approach to debugging complex distributed systems, mentoring team members in writing high-quality, maintainable software, and driving a strong technical culture.
- Autonomy: primarily autonomous and capable of being given tasks without excessive detail, able to figure out what to do and execute.

## #LI-HB1

## What we offer

- Flexible work organization
- Friendly and informal working environment
- Opportunity to work with an international team with high technical and scientific backgrounds

Recruitment Process & Security

- Please complete the form and submit your CV.
- 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.
- 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:
- Legitimate Owkin recruitment processes include communication with candidates through recognized professional networks, such as LinkedIn.
- Communication is always through an official Owkin email address (from the @[owkin.com](http://owkin.com) domain), over the phone or through our applicant tracking system (Greenhouse).
- 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 @[Owkin.com](http://Owkin.com).
- 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;
- 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
- 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.

If you think that you have been a victim of fraud,

- Check the identity of the talent team on LinkedIn
- Check our senior team on our website https://owkin.com/team/
- Check the existence of the position on our website: https://www.owkin.com/careers#current-opportunities
- Notify Owkin's recruitment unit at this address hiring@owkin.com
- contact the following authorities:
- [FR] https://internet-signalement.gouv.fr/
- [UK] https://www.actionfraud.police.uk/reporting-fraud-and-cyber-crime
- [US] https://reportfraud.ftc.gov/

## About Owkin

## Company Overview
- **One-liner**: Owkin is building an autonomous AI Scientist to automate biopharma R&D and support clinical research, aiming for Biological Artificial Superintelligence.
- **Entity Type**: Private (venture-backed; raised $304M from leading biopharma companies and venture funds)
- **Headquarters**: Paris, France (with offices in Boston, New York, London, Nantes, Geneva, and Berlin)
- **Founded**: 2016
- **Founders**: Thomas Clozel, MD (clinical oncologist) and Gilles Wainrib, PhD (machine learning pioneer)

## Core Business
- **Primary industries**: AI-driven drug discovery, diagnostics, and biomedical research
- **Target customers**: Biopharma companies (top 8 global biopharmas), clinical researchers, and oncology specialists (B2B, enterprise)
- **Mission**: To build an autonomous AI Scientist that exceeds human performance across life science domains, enabling faster and smarter drug discovery decisions

## Products & Services
- **K Pro**: An AI agent connecting research and care, integrating biological large language models, multimodal patient data, and a decade of biomedical AI expertise. It continuously learns from real-world data and clinical validation, evolving toward fully automated R&D.
- **Diagnostics (via spin-out Waiv)**: First-in-class AI diagnostics including:
  - **RlapsRisk® BC**: CE-marked prognostic risk profiling for breast cancer
  - **MSIntuit® CRC**: CE-marked MSI screening for colorectal cancer
  - **BRCAura RUO**: Research-use-only tool to predict germline BRCA1/2 mutations from HR+/HER2- breast cancer images

## Market Standing
- **Valuation/Market Cap**: Not publicly disclosed
- **Key Metric**: $304 million total funding raised (from Sanofi, BMS, F-Prime Capital, Google Ventures, Bpifrance Large Ventures, among others)
- **Notable Investors/Partners**: Sanofi (AI drug discovery deal), Bristol Myers Squibb (AI drug development), MSD (AI diagnostics), and a Scientific Advisory Board chaired by Prof. Miriam Merad, MD, PhD
- **Growth Signals**:
  - Strategic deals with three of the top global biopharmas
  - 104 academic partners across Canada, USA, France, Germany, Spain
  - Publications in top journals (Nature Medicine, Nature Communications, Hepatology)
  - Team of 200+ (now 357 employees as of latest data) with 20+ PhDs and 23 nationalities

## Competitive Advantages
- **Multimodal patient data network**: The world’s richest multimodal patient data network, trained and validated through a wet lab infrastructure and a global network of leading oncologists and biologists
- **Autonomous AI Scientist vision**: K Pro is designed to achieve true causal understanding of disease, moving beyond pattern recognition to hypothesis generation and automated R&D
- **Deep biopharma partnerships**: Strategic deals with top pharma (Sanofi, BMS, MSD) provide both funding and real-world validation
- **Founder-led and scientifically robust**: Co-founded by a clinical oncologist and a machine learning professor; strong Scientific Advisory Board with high H-index KOLs

## Strategic Focus
- **Current priorities**: Scaling K Pro as the one AI Scientist for biopharma R&D, expanding diagnostic spin-out Waiv, and deepening partnerships with top pharma companies
- **Direction**: Achieving Biological Artificial Superintelligence – an autonomous, self-improving AI system capable of running large parts of drug discovery independently

## Why Work Here
- **Culture**: Values curiosity, care, collaboration, and creativity. Described as a place for people who ask “why?”. Multidisciplinary team spanning machine learning, statistics, medicine, and biology.
- **Remote/Hybrid/Office**: Flexible working options – office, hybrid, and remote. All-company offsites twice a year, regular team offsites, learning sessions, and internal hackathons.
- **Perks**:
  - 35 days vacation plus public holidays
  - Minimum 16 weeks paid parental leave for primary caregivers, 8 weeks for secondary (gender-neutral)
  - Private healthcare coverage tailored to country
  - Opportunity to work from anywhere in the world for up to 4 weeks per year
- **Team composition**: 357 employees, 23 nationalities, 45/55 female/male split (2022 Professional Equality Index score 93/100 in France), 20+ PhDs

## Sources
1. [Owkin.com](https://www.owkin.com/)
2. [Owkin About Us](https://www.owkin.com/about-us)
3. [Owkin Careers](https://www.owkin.com/careers)
4. [Owkin People](https://www.owkin.com/people)
5. [Owkin Hiring (Greenhouse)](https://boards.eu.greenhouse.io/owkin)

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