Strong knowledge of Data Mining and data preparation techniques for Machine Learning and Deep Learning algorithms.
Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, Engineering, or a related field.
Experience with Machine Learning and Deep Learning techniques in solution development.
Ability to analyze complex issues and develop effective solutions.
Knowledge of Natural Language Processing (NLP), including semantic search, text processing, and conversational AI applications.
Good communication and interpersonal skills.
Qualification wording
Strong knowledge of Data Mining and data preparation techniques for Machine Learning and Deep Learning algorithms.
Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, Engineering, or a related field.
Experience with Machine Learning and Deep Learning techniques in solution development.
Ability to analyze complex issues and develop effective solutions.
Knowledge of Natural Language Processing (NLP), including semantic search, text processing, and conversational AI applications.
Good communication and interpersonal skills.
Education & alternatives
Profile:
- Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, Engineering, or a related field.
- Minimum 5 years of experience in Data Analytics, Data Engineering, or Information Systems.
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
Python
Azure
Databricks
Docker
Power BI
Spark
PyTorch
TensorFlow
Where the posting names them
- Knowledge of Natural Language Processing (NLP), including semantic search, text processing, and conversational AI applications.
- Experience with data science and analytics technologies such as Python, Haystack, TensorFlow, PyTorch, Jupyter Notebook, and related frameworks.
- Strong understanding of data engineering and data processing pipelines (ETL, APIs, Azure Databricks, Spark).
- Implement machine learning models (supervised and unsupervised) for recommendation systems, classification, and predictive analytics.
- Design and optimize data ingestion and transformation pipelines in cloud environments (Azure, Databricks, APIs).
- Perform data modelling, data analysis, and dataset preparation for machine learning and AI solutions.
- Experience with data science and analytics technologies such as Python, Haystack, TensorFlow, PyTorch, Jupyter Notebook, and related frameworks.
- Strong understanding of data engineering and data processing pipelines (ETL, APIs, Azure Databricks, Spark).
- Good knowledge of data modelling, data warehouse, and data lake architectures.
- Experience with BI and reporting tools, such as Power BI.
- Knowledge of Docker containerization, virtualization, and deployment is an asset.
- Knowledge of Agile and Scrum methodologies is an asset.
- Contribute to the design of data lake architectures and ETL processes (Bronze/Silver/Gold layers).
- Develop analytics and reporting solutions, including Power BI dashboards.
- Participate in technical working groups, progress meetings, and meetings with users.
- Good knowledge of data modelling, data warehouse, and data lake architectures.
- Experience with BI and reporting tools, such as Power BI.
- Knowledge of Docker containerization, virtualization, and deployment is an asset.
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
US government figures for computer and information research scientists
Median yearly pay, May 2025
$140,300
Expected change, 2025 to 2035
21.8% more jobsagainst 3.5% for all jobs
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
We are continuously looking for talented AI & Data Engineers to join our talent pool and support future projects with our clients. This is a generic and ongoing opportunity aimed at identifying experienced professionals for upcoming assignments.
You will contribute to the design, development, and deployment of innovative Artificial Intelligence, Business Intelligence, and Data Analytics solutions. You will work closely with business and technical stakeholders to transform complex data into actionable insights and intelligent applications leveraging Machine Learning, NLP, Generative AI, and cloud-based data platforms.
Responsibilities:
Provide expert advice and assistance, technology watch, evaluation studies, architectural considerations, applicable standards, solution patterns, and best practices in the areas of Business Intelligence, Data Analytics, and Artificial Intelligence.
Design, develop, and deploy AI-powered applications using Retrieval-Augmented Generation (RAG) and LLM-based architectures.
Develop NLP pipelines for document processing, summarization, semantic search, and conversational AI.
Implement machine learning models (supervised and unsupervised) for recommendation systems, classification, and predictive analytics.
Design and optimize data ingestion and transformation pipelines in cloud environments (Azure, Databricks, APIs).
Perform data modelling, data analysis, and dataset preparation for machine learning and AI solutions.
Integrate AI solutions with existing enterprise systems and data platforms.
Contribute to the design of data lake architectures and ETL processes (Bronze/Silver/Gold layers).
Develop analytics and reporting solutions, including Power BI dashboards.
Participate in technical working groups, progress meetings, and meetings with users.
Assist during testing, analysis, technical documentation, deployment, evaluation, and reporting activities.
Technical skills:
Strong knowledge of Data Mining and data preparation techniques for Machine Learning and Deep Learning algorithms.
Experience with Machine Learning and Deep Learning techniques in solution development.
Knowledge of Natural Language Processing (NLP), including semantic search, text processing, and conversational AI applications.
Experience with data science and analytics technologies such as Python, Haystack, TensorFlow, PyTorch, Jupyter Notebook, and related frameworks.
Strong understanding of data engineering and data processing pipelines (ETL, APIs, Azure Databricks, Spark).
Good knowledge of data modelling, data warehouse, and data lake architectures.
Experience with BI and reporting tools, such as Power BI.
Knowledge of Docker containerization, virtualization, and deployment is an asset.
Knowledge of Agile and Scrum methodologies is an asset.
Good knowledge of architecture best practices and patterns.
Profile:
Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, Engineering, or a related field.
Minimum 5 years of experience in Data Analytics, Data Engineering, or Information Systems.
Minimum 3 years of experience in BI and reporting solutions.
Minimum 2 years of hands-on experience in Prompt Engineering for Large Language Models (LLMs).
Ability to analyze complex issues and develop effective solutions.
Good communication and interpersonal skills.
Strong analytical mindset and attention to detail.
Ability to work in a multicultural and international environment.
Fluency in English is required, French is a strong asset.
Why Cronos Group?
We’ll propose you:
An attractive salary package.
A good work-life balance environment.
The assurance of working in cutting-edge technologies in an entrepreneurial spirit.
The opportunity to develop your skills thanks to tailor-made training courses according to your needs.
A good job in a friendly place.
If you wish to integrate a dynamic structure on a human scale while working with the latest technologies, don't wait anymore and join Cronos!