Staff MLOps Engineer

il y a 2 semaines

Paris, Île-de-France Doctolib Temps plein
About the Role

We are seeking a highly skilled and motivated MLOps Engineer to join our ML Platform Team at Doctolib. As a key member of our team, you will play a pivotal role in developing, deploying, and maintaining machine learning models and systems, ensuring their performance and scalability.

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.
Requirements
  • 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.
  • 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.
  • Proficient in our core languages: 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.
  • Experience with MLOps Frameworks like MLFlow/Kubeflow.
  • 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,...).
  • Familiar 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.
Preferred Qualifications
  • Experience with Kubernetes, GitOps tools (e.g. ArgoCD), and/or Kafka.
  • Experience with Terraform Enterprise/Hashicorp Vault/Cloudflare.
  • Experience developing in Javascript/Typescript and using deployment in the browser.
  • Experience with ML model quantization and optimization.
About 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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