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ML-OPS Lead H/F

Qantev is hiring!

About

Qantev is the most advanced AI Platform dedicated to helping health insurers deliver superior healthcare and claims experience to their members. By leveraging insurers' historical health claims data and applying advanced Machine Learning techniques and Generative AI, Qantev predicts patient journeys, optimizes healthcare outcomes and streamlines healthcare payers operations.

Founded in 2018 and backed by top investors and industry leaders, Qantev has over 60 talented and diverse professionals based in Paris and Hong Kong, serving clients across Europe, the United States, Latin America, Asia, and the Middle East.

If you are passionate about technology and the insurance industry, join Qantev and be a part of revolutionizing the insurance claims landscape with AI-driven solutions!

We are currently recruiting for our Paris office, a ML-OPS Lead H/F (CDI)

Job Description

About the role 🚀

In addition to the responsibilities of being the MLOps lead at Qantev, you will get an opportunity to:

  • Set the guidelines and standards of MLOps at the company

  • Design and manage ML pipelines, from data ingestion and model training to deployment and monitoring

  • Ensure safe, stable and performant deep learning model deployment in both real-time and batch flows, considering latency, reliability and scalability

  • Implement best practices for version control, CI/CD, and model reproducibility for the ML/DL models

  • Develop and maintain infrastructure for automated model training and retraining.

  • Monitor model performance and implement alerting mechanisms to identify issues such as data-drift and others.

  • Collaborate with data scientists and software engineers to optimize ML workflows.

  • Manage cloud infrastructure and resources to support ML workloads efficiently

Preferred Experience

Your Profile:

  • At least 5 years of experience in MLOps, DevOps or software engineering, with focus on ML/AI systems.

  • Strong experience with cloud platforms (AWS, Azure, GCP) and their ML services.

  • Proven experience in deploying and managing ML models in production.

  • Strong programming skills in Python, Linux (Bash) and proficiency with ML frameworks like PyTorch, HuggingFace, ONNX, etc.

  • Strong knowledge of containerization (Docker) and orchestration tools (Kubernetes).

  • Experience with CI/CD pipelines, monitoring tools, and version control (Git).

  • Familiarity with data pipeline tools (Airflow, Apache Kafka, Dagster) and model monitoring frameworks.

  • Expertise in managing and optimizing cloud-based resources for ML workloads.

  • Strong communication and presentation skills, with the ability to convey complex concepts to non-technical audiences

  • Experience in developing APIs

  • Experience with ML versioning tooling, including data versioning and model registries.

  • Fluent in English (Both Verbal and written). Any additional language is a plus

Bonus skills:

  • Experience in the health insurance industry

  • Experience with setting up and managing GPUs for Accelerated Deep Learning

  • Strong background on Deep Learning

Benefits of Working At Qantev:

You’ll join a team of highly skilled and motivated individuals who are willing to share their knowledge and passion for advanced data science, machine learning and computer science. In addition to this we provide:

  • Competitive compensation & Equity stake in the company

  • Opportunity to take part in scaling a global tech start-up

  • Opportunity to be a part of a fun, dynamic and exuberant environment!

  • Beautiful office in the heart of the 9th arrondissement of Paris

  • Annual company off-site

  • Start-up ecosystem benefits

    • New Macbook
    • Alan Blue Health Insurance
    • Swile (daily lunch vouchers & gift cards)
    • Navigo reimbursement

Recruitment Process

  • Screening interview

  • Tech Interview 1: Machine/Deep Learning

  • Tech Interview 2: Infra/Software/Devops/MLOps

  • Fit validation interview (On Site)

Additional Information

  • Contract Type: Full-Time
  • Location: Paris
  • Possible partial remote
Apply Now