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ML Ops Lead

Qantev is hiring!

About

Qantev is an AI company that helps health insurers deliver better healthcare to their members.

They do that by leveraging insurers’ historical health claims data and by applying Machine Learning techniques and Generative AI to predict patient journeys.

They are backed by top investors and industry leaders, and have customers all across the world (Europe, USA, LATAM, Asia and the Middle East).

They are a growing team of talented, enthusiastic, and diverse professionals. As an early hire, you will have an unparalleled opportunity for ownership and growth within the company.

Job Description

RESPONSIBILITIES

  • 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


REQUIREMENTS

  • +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.

  • Fluency in English. 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


HIRING PROCESS

  • Interview with the Talent Acquisition Leader

  • Tech Interview 1: Machine/Deep Learning

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

  • Interview with the VP of Engineering

Additional Information

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