AI Expert

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Goals & Performance Metrics:

Key Goal Areas:

Model Development & Performance:
Goal: Develop and deploy high-performing AI models that meet specific business objectives.
Performance Metrics:
Model accuracy, precision, recall, F1-score, and other relevant metrics.
Model training time and computational efficiency.
Speed of model deployment.
Number of models successfully deployed into production.
Innovation & Research:
Goal: Drive innovation by researching and implementing cutting-edge AI techniques.
Performance Metrics:
Number of novel AI solutions proposed and implemented.
Participation in research publications or conferences.
Contribution to the company's AI intellectual property.
Exploration and implementation of new AI tools and techniques.
Data Analysis & Insights:
Goal: Extract valuable insights from data to support business decision-making.
Performance Metrics:
Quality and relevance of insights generated.
Impact of insights on business outcomes.
Efficiency in data processing and analysis.
Number of valuable data driven reports.
Collaboration & Communication:
Goal: Effectively collaborate with technical and business teams to integrate AI solutions.
Performance Metrics:
Effectiveness of communication with stakeholders.
Ability to translate technical concepts into business language.
Contribution to team projects and knowledge sharing.
Feedback from other teams.
Continuous Learning & Development:
Goal: Stay up-to-date with the latest advancements in AI and continuously improve technical skills.
Performance Metrics:
Participation in relevant training and certifications.
Demonstrated ability to apply new knowledge to projects.
Contribution to internal knowledge sharing sessions.
Number of new tools or techniques learned.
Specific Performance Indicators:

Percentage improvement in model accuracy.
Reduction in model training time.
Number of AI-driven features launched.
Number of data-driven insights that lead to measurable business improvements.
Number of successful collaborations with other teams.
Number of new AI technologies mastered.
Number of code reviews completed, and their quality.

N+1 Management Style:

The N+1 Manager is involved in day-to-day operations, providing guidance and support to ensure smooth delivery processes.
Regular performance reviews and constructive feedback are provided to help teams improve and excel in their roles.

Career Progression Opportunities:

Internal Mobility
Skill Development

Benefits & Culture:

Work-Life Balance
Inclusive Culture

Candidate Selection Criteria:

Core Technical Expertise:

Advanced Educational Background:
Ph.D. or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related field.
Specialized coursework and research in AI subfields (e.g., deep learning, NLP, computer vision, reinforcement learning).

Programming Proficiency:
Expertise in Python, R, Scala, or other relevant programming languages.
Strong understanding of AI/ML libraries and frameworks (TensorFlow, PyTorch, scikit-learn).

Machine Learning Expertise:
Deep understanding of various ML algorithms (supervised, unsupervised, reinforcement learning).
Ability to select and apply appropriate algorithms for specific problems.
Experience in model training, evaluation, and optimization.

Data Science Skills:
Proficiency in data analysis, data preprocessing, and feature engineering.
Experience working with large datasets and data pipelines.
Knowledge of statistical methods and techniques.

Specialized AI Knowledge (as needed):
Natural Language Processing (NLP): Text mining, sentiment analysis, language modeling.
Computer Vision: Image recognition, object detection, video analysis.
Deep Learning: Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Transformers.
Reinforcement Learning: experience building agents, and working with reward functions.

Cloud Computing and Infrastructure:
Familiarity with cloud platforms (AWS, Azure, GCP) and their AI/ML services.
Experience deploying and scaling AI models in cloud environments.

Knowledge of AI Ethics and Responsible AI:
Understanding of biases in AI, and how to mitigate them.
Knowledge of responsible AI principals.

Essential Soft Skills:

Problem-Solving and Analytical Skills:
Ability to break down complex problems into smaller, manageable tasks.
Strong analytical and critical thinking skills.
Ability to identify and resolve technical challenges.

Communication Skills:
Ability to communicate complex technical concepts clearly and concisely to both technical and non-technical audiences.
Excellent written and verbal communication skills.
Ability to present research findings and project updates effectively.

Collaboration and Teamwork:
Ability to work effectively in cross-functional teams.
Willingness to share knowledge and expertise.

Creativity and Innovation:
Ability to think creatively and develop innovative AI solutions.
Passion for exploring new AI technologies and applications.

Continuous Learning:
Ability to stay up-to-date with the latest AI research and advancements.
Willingness to learn new technologies and techniques.

Other Important Criteria:

Research and Publications:
Publications in reputable AI conferences and journals (if applicable).
Contributions to open-source AI projects.

Industry Experience:
Proven track record of success in developing and deploying AI solutions in a professional setting.

Portfolio:
A portfolio of AI projects demonstrating technical skills.

Desired Profile:

Education: Advanced degree in computer science, mathematics, statistics, or equivalent, with a specialization in artificial intelligence or machine learning.
Experience: Minimum of 1 year of professional experience in a similar position.

Technical Skills: Proficiency in programming languages Python, R, Scala; expertise in machine learning algorithms (neural networks, supervised, unsupervised, reinforcement learning), natural language processing (NLP), computer vision, etc.

Soft Skills: Creativity, curiosity, scientific rigor, analytical skills, synthesis skills, excellent communication skills, autonomy, ability to work in a team.

Work condition:

8h15 - 17h
Monday to Friday

Message from your future manager N+1:

Join our team as an AI Expert in an expanding company and become a key part of a dynamic, customer-focused operation. We encourage all interested candidates to apply, as all applications will be evaluated.
Let's meet to talk about it !