Machine Learning Engineer

il y a 3 semaines


Paris, Île-de-France Oppizi Temps plein
Machine Learning Engineer

We are seeking a highly skilled Machine Learning Engineer to join our dynamic team at Oppizi. As a key member of our technology division, you will play a vital role in developing, deploying, and optimizing end-to-end machine learning models.

Key Responsibilities:
  • Model Development and Deployment: Design, implement, and deploy machine learning models that address business needs, ensuring high availability and performance in production environments.
  • MLOps and Automation: Apply MLOps best practices to automate the ML lifecycle, including data ingestion, training, and deployment pipelines. Build and maintain CI/CD pipelines for continuous integration and delivery.
  • Performance Monitoring and Optimization: Monitor deployed models to ensure they meet performance metrics, and continuously improve them for accuracy and scalability.
  • Collaboration and Communication: Work closely with software engineers, product managers, and other stakeholders to develop and communicate ML solutions effectively.
Requirements:
  • Education: Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, or a related field.
  • Experience: Minimum of 4 years of experience as a Machine Learning Engineer or in a similar role.
  • MLOps Expertise: Proven experience with MLOps tools and frameworks (e.g., MLflow, Kubeflow, TensorFlow Extended).
  • Programming Skills: Strong proficiency in Python and experience with libraries such as Pandas, NumPy, and Scikit-learn.
  • Cloud & Containerization: Hands-on experience with cloud platforms like AWS, Azure, or Google Cloud, and familiarity with containerization technologies like Docker and Kubernetes.
  • Data & API Proficiency: Experience with data manipulation and building APIs using frameworks such as FastAPI, Flask, or Django.
  • Communication Skills: Ability to explain complex technical concepts to both technical and non-technical stakeholders.
Benefits:
  • Competitive Salary: Open to negotiation with performance-based bonuses.
  • Professional Growth Opportunities: In a fast-growing startup.
  • Flexible Working Hours: And remote work options.

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