Machine Learning Engineer

il y a 3 semaines


Paris, Île-de-France Oppizi Temps plein

We are seeking a talented Machine Learning Engineer to collaborate with our dynamic technology team. As a key contributor, you will be responsible for developing, deploying, and optimizing end-to-end machine learning models.

This role demands expertise in MLOps and the ability to handle the entire machine learning lifecycle, from data ingestion to model deployment and beyond.

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.

To succeed in this role, you will require:

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.
  • 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 and containerization technologies.
  • Data & API Proficiency: Experience with data manipulation and building APIs.
  • Communication Skills: Ability to explain complex technical concepts to both technical and non-technical stakeholders.

We offer a competitive salary, performance-based bonuses, professional growth opportunities, and flexible working hours.



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