This list contains only the countries for which job offers have been published in the selected language (e.g., in the French version, only job offers written in French are displayed, and in the English version, only those in English).
Lead the design and architecture of machine learning solutions for complex business problems
Collaborate with business stakeholders to understand their requirements and define the overall technical strategy, including model selection, data pre-processing, feature engineering, and model evaluation
Design and implement scalable and efficient data pipelines to collect, preprocess, and store large volumes of data for machine learning projects
Develop data transformation and feature extraction processes to prepare data for machine learning model training and deployment
Lead the development of advanced machine learning models using state-of-the-art algorithms, such as deep learning, reinforcement learning, and other cutting-edge techniques
Optimize model performance through hyperparameter tuning, model validation, and feature selection
Drive the deployment of machine learning models in production environments, ensuring scalability, reliability, and security
Implement monitoring and logging mechanisms to capture and analyze model performance data
Make necessary adjustments to ensure optimal performance and accuracy
Provide technical leadership and mentorship to a team of data scientists, engineers, and other stakeholders
Guide and mentor junior team members, provide technical expertise and advice, and drive innovation in the field of machine learning
Stay updated with the latest developments in the field of machine learning and artificial intelligence
Identify and evaluate new technologies, tools, and techniques for improving machine learning models and systems
Drive innovation and experimentation to push the boundaries of machine learning capabilities
Collaborate closely with cross-functional teams, including data scientists, engineers, and business stakeholders, to understand requirements, provide technical guidance, and ensure successful implementation of machine learning solutions
Collaborate with business stakeholders to identify new opportunities for leveraging machine learning for business success
Create documentation, technical specifications, and reports related to machine learning solutions, including model design, data pipeline architecture, deployment process, and performance metrics
Present findings and recommendations to stakeholders in a clear and concise manner
Requirements:
Master's or PhD degree in Computer Science, Statistics, Mathematics, or a related field
8+ years of relevant experience in machine learning and artificial intelligence
Proven experience in designing, developing, and implementing advanced machine learning solutions for complex business problems
Strong programming skills in languages such as Python, R, or Java, and deep understanding of machine learning libraries such as TensorFlow, PyTorch, or scikit-learn
Extensive experience with machine learning algorithms, including deep learning, reinforcement learning, and other cutting-edge techniques
Strong knowledge of data preprocessing, feature engineering, and data visualization techniques
Excellent understanding of machine learning model performance metrics and optimization techniques
Experience with designing and implementing scalable data pipelines and working with big data technologies
Proven experience with deploying machine learning models in production environments, and implementing monitoring and logging mechanisms for performance analysis
Strong leadership and mentoring skills, with the ability to provide technical guidance and mentor junior team members
Excellent problem-solving skills and ability to work in a fast-paced, collaborative environment
Strong communication and presentation skills, with the ability to effectively communicate complex technical concepts to non-technical stakeholders
Proven ability to drive innovation, research new technologies, and push the boundaries of machine learning capabilities
Ethical mindset and commitment to ensuring compliance with data privacy, security, and ethical considerations in machine learning projects