What you’ll do
At Doctolib, we're on a mission to transform the way healthcare is delivered by leveraging the power of AI.
We are seeking a highly skilled, motivated, and collaborative MLOps Engineer to join our 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. 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.
Your responsibilities include but are not limited to:
- 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
- Share & advocate your work with the tech community
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
And any other tool you deem relevant!
Who you are
If you don’t meet all the requirements below but believe this opportunity matches your expectations and experience, we still encourage you to apply!
You could be our next team mate if you:
- Have a good team spirit, enjoy learning new skills and have a strong sense of initiative
- Excellent communication and collaboration skills, with the ability to work well in cross-functional teams and write clear documentation.
- Have a Bachelor's degree in Computer Science, Engineering, or a related field; advanced degree preferred
- Have a proven experience (5 years) as an MLOps Engineer, Cloud engineer for Machine Learning applications or similar role.
- Are proficient in our core languages : Python / SQL / Shell Scripting / Terraform
- Have a strong knowledge of machine learning algorithms / concepts / trends
- Have an expertise in Deep Learning Framework, preferably PyTorch
- Have strong knowledge of cloud platforms like AWS and services like Amazon SageMaker, EC2, ECS, S3, CloudWatch and/or Azure and GCP equivalents.
- Have experience in building with HuggingFace Technologies, including Transformers, Diffusers, Accelerate, PEFT
- Have experience in building MLOps pipelines for containerizing models and solutions with Docker
- Have experience with MLOps Frameworks like MLFlow / Kubeflow
- Are proficient in “classic” DevOps: strong experience with setting up CI/CD systems with declarative pipelines (GitHub Actions), monitoring, dev-qa-prod environments
- Have experience in version control and application/library packaging tools (Git, Poetry, Docker, …)
- Are familiar with Apache Spark or other big data processing frameworks.
- have experience with GPU programming (CUDA) and optimization for cost and speed
- Have Knowledge of back-end and middleware services, such as NGINX, FastAPI, or Airflow
Now, it would be fantastic if you:
- Have experience with Kubernetes, GitOps tools (e.g. ArgoCD) and/or Kafka
- Have experience with Terraform Enterprise / Hashicorp Vault / Cloudflare is a plus
- Have experience developing in Javascript / Typescript and using deployment in the browser (transformers.js / langchain.js)
- Have experience with ML model quantization and optimization
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 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
The interview process
- HR interview by phone (45 minutes)
- Hiring manager interview (1 hour)
- Case study & case restitution (1 hour)
- Pairs interview / Meet the team session (1 hour / half day immersion)
- At least one reference check
- A copy of your criminal records (“extrait de casier judiciaire B3”)
Job details
- Permanent position
- Full Time
- Workplace : Paris area
- Start date: asap
- Remuneration : fix + bonus on objectives (according to your profile)
A stock options plan for every Doctoliber
At Doctolib, we believe in improving access to healthcare for everyone - regardless of where you come from, what you look like. This translates into our recruitment process: Doctolib is an equal opportunity employer. We don't just accept diversity at Doctolib, we respect and celebrate it!
The more diverse ideas are heard, the more our product will truly improve healthcare for all. You are welcome to apply to Doctolib, regardless of your gender, religion, age, sexual orientation, ethnicity, disability, or place of origin. If you have a disability, let us know if there's any way we can make the interview process smoother for you!
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