Senior Data Scientist/MLOps, Plain Concepts

• We are looking for a passionate engineer with background in machine/deep learning
• More than 5 years of experience in AI / Machine Learning / Computer Science
• Can build an “end-to-end software product” which has machine learning component
• Knowledges in applied computer vision
• Strong skills in Python and reasonable SQL understanding
• Experience in building ML/deep learning pipelines and models
• Experience in implementing production ready ML models using current ML/Deep learning techniques
• MLOps experience is mandatory for the team
• Experience in projects with NLP/Gen IA is neccesary
• Very valuable your international and presales experience
• ENGLISH IS MANDATORY

Desirable

• We are expanding our development teams and although we don’t care much about titles, we call this role Senior Data Scientist
• As an Data Scientist Engineer, you will be part our international AI/ML team developing tailored solutions to satisfy our client's needs
• You will be training, and deploying models, putting research into production, among other tasks
• You will be part of a multidisciplinary team, taking care of the software engineering challenges associated with AI. You will take part in challenging projects using cutting edge technologies. You will work in an international environment with the possibility of working from home or from our offices
• Our vision is to build multidisciplinary teams which directly manage projects in an AGILE way to find and implement the best solutions
• Participating in the design and development of AI solutions for challenging projects
• Building production level ML/AI solutions, with solid software engineering and ML/AI principles
• MLOps Automated deployment and monitoring (models and infrastructure)
• Data analysis (data cleaning, variable transformation, etc.)
• Developing and training ML models
• Putting AI models into production
• This means parallelizing, optimizing, tuning, testing the models to deploy in a production environment

• The selection process? Simple, just 3 steps: a call and 2 interviews with the team