Doctolib

Job Description:

Job description

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 (2 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 ( 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 ( /

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

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!