MLOps Engineer
il y a 1 semaine
About the Role
We are seeking a highly skilled MLOps Engineer to join our ML Platform Team at Doctolib, a company on a mission to transform the way healthcare is delivered by leveraging the power of AI.
The successful candidate will play a pivotal role in developing, deploying, and maintaining machine learning models and systems, ensuring their performance and scalability. You 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.
Key Responsibilities
- Collaborate with data scientists and engineers to develop and deploy machine learning models, ensuring they meet performance, scalability, and reliability requirements.
- Implement and maintain the MLOps pipeline, including version control, continuous integration, continuous deployment, and monitoring of machine learning models.
- Develop tools, frameworks, and best practices to streamline the model development and deployment process.
- Ensure the availability, reliability, and performance of machine learning models and systems, proactively addressing any issues that arise.
- Monitor the performance of machine learning models in production, identifying areas for improvement and working with data scientists to optimize the models.
- Stay up-to-date with the latest advancements in MLOps and machine learning technologies, incorporating them into the ML Platform Team's workflows as appropriate.
- Collaborate with cross-functional teams to gather requirements, provide technical guidance, and contribute to the development of machine learning solutions.
- Document MLOps processes, standards, and best practices to ensure knowledge transfer and consistency across the team.
Our Stack
- Programming languages: Python, PySpark, SQL.
- Cloud providers: AWS, Azure.
- Machine Learning platform: AWS SageMaker.
- Container/Orchestration: AWS ECS, Docker.
- Data warehouse/storage: AWS S3, AWS Redshift.
- Databases: PostgreSQL.
- Search engine: ElasticSearch.
- Data capture tool: AWS Kinesis.
- ML pipeline: AWS Step Functions, AWS Lambda, AWS SageMaker.
- Infrastructure as code: Terraform.
What We Offer
- A stock-option program for each Doctoliber.
- 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.
- 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.
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