Scientist II, Machine Learning Engineer – LLM, GenAI Specialist

OWKIN

. Design, develop, and deploy cutting-edge AI solutions .

Posted 10/9/2026full-timeParis • FranceMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in designing and deploying AI solutions, with a strong focus on machine learning algorithms and frameworks such as PyTorch and TensorFlow. Proven ability to optimize workflows and manage the end-to-end model lifecycle in a collaborative environment.

Highest-signal resume keywords

Master’s Or Ph.D. In Computer Science5+ Years Of Professional Experience In Software DevelopmentProven Track Record Of Deploying Deep Learning ModelsMastery Of PyTorch Or TensorFlowExperience With AWS, GCP, Or Azure

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine Learning AlgorithmsDeep Learning FrameworksExperiment Tracking SystemsDistributed ComputingML Workflow OptimizationStatistical MethodsGenerative AIVersion ControlCI/CDDocker

Soft Skills

Problem-Solving SkillsStrong Communication SkillsProactive DebuggingMentoring Team MembersAbility To Work Autonomously

Tools & Technologies

Hugging FaceSageMakerAWSGCPAzure

Industry Keywords

Clinical DataOmics DataMedical Imaging ProcessingResearch WorkflowsOpen-Source ML Contributions

Tech Stack

Tools & technologies

AWSAzureDistributed SystemsDockerGoogle Cloud PlatformPythonPyTorchTensorflow

About the role

Key responsibilities & impact

Design, develop, and deploy cutting-edge AI solutions
Develop scalable machine learning libraries, tooling, and research workflows with research and data scientists
Shape research infrastructure requirements and collaborate with the platform team on tool and software choices
Champion software engineering best practices for maintainable, testable, efficient, and scalable code
Design and enhance systems for experiment tracking, reproducibility, and end-to-end model lifecycle management
Accelerate rapid prototyping of novel models and bridge early research with robust implementation
Perform other ad-hoc responsibilities, tasks, and projects assigned by management

Requirements

What you’ll need

Master’s or Ph.D. in Computer Science, Data Science, or a related quantitative field with a strong focus on ML/AI
5+ years of professional experience in software development with Python
Proven track record of deploying deep learning models into production
Deep understanding of machine learning algorithms, statistical methods, and deep learning frameworks
Mastery of PyTorch or TensorFlow
Deep understanding of Transformer architectures, attention mechanisms, and recent Generative AI breakthroughs
Extensive experience with Hugging Face
Knowledge of agentic workflows and RAG
Experience with AWS, GCP, or Azure and SageMaker
Experience with version control, comprehensive testing, CI/CD, and Docker
Experience with distributed computing and distributed training strategies for massive datasets
Experience optimizing ML workflows, such as vLLM
Experience with clinical or omics data and medical imaging processing and analysis is preferred
Contributions to open-source ML projects or research publications are preferred
Excellent problem-solving skills
Strong communication skills
Proactive approach to debugging complex distributed systems and mentoring team members
Ability to work autonomously
CV must be submitted in English
Comfortable speaking and writing English daily in an international environment

Benefits

Comp & perks

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