Senior ML Ops Engineer (x/f/m)

Job Description

Doctolib is seeking a Senior MLOps Engineer to join its ML Platform Team. The successful candidate will play a pivotal role in developing, deploying, and maintaining machine learning models and systems, ensuring their performance and scalability. He/She will collaborate with data scientists, software engineers, platform engineers and other stakeholders to deliver high-quality solutions that power Doctolib products for care teams and patients.

Role involves:

• Collaborating with data scientists and engineers to develop and deploy machine learning models.
• Implementing and maintaining the MLOps pipeline.
• Developing tools, frameworks, and best practices to streamline the model development and deployment process.
• Ensuring the availability, reliability, and performance of machine learning models and systems.
• Monitoring the performance of machine learning models in production.
• Staying up-to-date with the latest advancements in MLOps and machine learning technologies.
• Collaborating with cross-functional teams to gather requirements, provide technical guidance, and contribute to the development of machine learning solutions.
• Documenting MLOps processes, standards, and best practices.
• Share & advocate your work with the tech community

Requirements:

• Good team spirit, enjoy learning new skills and have a strong sense of initiative.
• Excellent communication and collaboration skills.
• Bachelor's degree in Computer Science, Engineering, or a related field; advanced degree preferred.
• Proven experience (5 years) as an MLOps Engineer, Cloud engineer for Machine Learning applications or similar role.
• Proficiency in Python / SQL / Shell Scripting / Terraform.
• Strong knowledge of machine learning algorithms / concepts / trends.
• Expertise in Deep Learning Framework, preferably PyTorch.
• Strong knowledge of cloud platforms like AWS and services like Amazon SageMaker, EC2, ECS, S3, CloudWatch and/or Azure and GCP equivalents.
• Experience in building with HuggingFace Technologies, including Transformers, Diffusers, Accelerate, PEFT.
• Experience in building MLOps pipelines for containerizing models and solutions with Docker.
• Proficient in “classic” DevOps: strong experience with setting up CI/CD systems with declarative pipelines (GitHub Actions), monitoring, dev-qa-prod environments.
• Experience in version control and application/library packaging tools (Git, Poetry, Docker, …).
• Familiarity with Apache Spark or other big data processing frameworks.
• Experience with GPU programming (CUDA) and optimization for cost and speed.
• Knowledge of back-end and middleware services, such as NGINX, FastAPI, or Airflow.

What Doctolib offers:

• Quarterly bonuses and a competitive package
• A 6-month dedicated onboarding program - the Doctolib Academy
• Continuous training programs on all key competencies (English, soft skills, expertise)
• Transparent internal mobility opportunities you're welcome to apply for
• 2 days per year to help health charities and create a positive social impact - the Solidarity Days
• Mental health and wellbeing offer in partnership with moka.care
• The Doctolib Parent Care Program, including extended parental leave, meet-ups and inspiring conferences
• High-quality office spaces supporting collaboration, health and wellbeing
• A subsidy from the work council to refund part of the membership to a sport club or a creative class
• A competitive health insurance paid 100% by the company
• Subsidy for lunch and various food offers in our offices
• A flexible workplace policy offering both hybrid and office-based mode
• Flexibility days allowing to work in EU countries and the UK 10 days per year
• A support for relocation in case of international mobilities and new joiners arriving to France, Germany and Italy from another country