Data Scientist – Machine Learning & MLOps

We are seeking an experienced Machine Learning & MLOps Engineer to join a forward-thinking team driving advanced AI and data-driven product development. This role is ideal for someone passionate about building scalable ML solutions and contributing to the industrialization of machine learning projects.

Your Role:

As a Data Scientist, you will leverage descriptive and predictive analytics to solve complex business challenges, optimize user experience, and drive business growth. You will also contribute to the deployment and production of models, ensuring robustness and scalability across the ML lifecycle.

Key Responsibilities:

• Roadmap & Strategy: Identify opportunities for implementing ML and DL algorithms aligned with business priorities. Collaborate with product teams to co-define the strategic roadmap.
• Project Framing: Define objectives, scope, methodology, and industrialization plans for projects, ensuring alignment across business and technical teams.
• Model Development & Deployment: Build, deploy, and monitor ML and DL models to address business problems, improve user satisfaction, and optimize features.
• Feature Engineering & Data Pipelines: Develop online computation and stateful feature management systems, as well as pipelines to accelerate model lifecycles.
• MLOps & Production: Implement CI/CD pipelines, model versioning, and monitoring. Contribute to the continuous improvement of the Data Science stack and industrialization on cloud platforms.
• Validation & A/B Testing: Conduct robustness tests, design experiments, and analyze A/B tests to measure the impact of models and product changes.
• Collaboration & Communication: Present findings clearly to stakeholders and mobilize teams around data-driven insights.

Ideal Candidate Profile:

• Strong proficiency in Python (and optionally Rust, C) and SQL
• Experience with Machine Learning, Deep Learning, and AI frameworks (TensorFlow, PyTorch, Scikit-Learn)
• Hands-on with LLM models, including fine-tuning, prompt engineering, evaluation, and production integration
• Experience with image processing, object detection, and image generation models
• Familiarity with cloud platforms (AWS, GCP, Azure), Docker, and Git
• Knowledge of data pipelines, feature platforms, and ML industrialization
• Experience in statistical testing, experimental design, and A/B testing best practices

Why This Role:

This role offers the opportunity to make a tangible impact by designing, building, and deploying ML solutions that shape product strategy and drive business value. You’ll work in a collaborative environment where your contributions directly influence innovation and user experience.