Join our Team
Location: Ottawa, Canada
Duration: 8 months
At this time, Ericsson Canada Inc. does not provide immigration assistance/sponsorship now or in the future for this position.
About this opportunity:
As the tech firm that created the mobile world—and with more than 54,000 patents to our name—Ericsson continues to lead the transformation of industries through connectivity, cloud computing, and artificial intelligence. At Ericsson, you’re empowered to explore cutting-edge technologies, learn from global experts, and make real impact on the future of intelligent networks and sustainable innovation.
Come be where the future begins.
We are seeking a highly motivated and research-driven intern currently pursuing a Master’s or PhD program in Computer Science, Software Engineering, Electrical Engineering, or a related field.
This internship provides hands-on across the entire AL/ML system development lifecycle including data processing, model training, data analytics, building robust data pipelines and deploying machine learning models in production. You will collaborate with multidisciplinary teams of AI researchers, data engineers, and software developers to explore, design, and deliver intelligent solutions for real-world network and business challenges.
What you will do:
AI/ML Development and Research
Research, design, and prototype advanced machine learning and deep learning models (e.g., transformers, graph neural networks, reinforcement learning, generative AI).
Build and train models using Python-based ML frameworks such as PyTorch, TensorFlow, Scikit-learn, or Hugging Face Transformers.
Experiment with foundation models (LLMs, diffusion models, or multimodal AI) for automation, data analysis, and knowledge discovery.
Conduct model evaluation, hyperparameter optimization, and performance benchmarking.
Contribute to MLOps workflows, applying best practices for the model deployment, monitoring, and automated retraining using tools like MLflow or
Kubeflow. Stay current with AI/ML research trends, and present key findings and innovation opportunities to the team.
Data Engineering and Analytics
Collect, clean, and structure large datasets from multiple internal and external sources.
Perform exploratory data analysis (EDA) to extract insights and identify meaningful patterns.
Develop interactive dashboards and visualizations using Power BI, Tableau, or Plotly Dash.
Collaborate with stakeholders to define and track data-driven KPIs and success metrics.
Improve data processing pipelines and contribute to automation and data governance best practices.
Perform model selection
Choose appropriate model architectures, validate design choices, and justify trade-offs between complexity, interpretability, and performance.
Conduct model evaluation
Design evaluation protocols, select relevant metrics, perform cross-validation, and analyze model performance, biases, and failure modes.
Work closely with cross-functional teams (AI research, software and hardware design) to design AI-driven use cases.
Present insights and model results to technical and non-technical audiences in a clear, impactful way.
Document methodologies, workflows, and experimental results to support reproducible research.
The skills you bring:
Currently pursuing a Master’s or PhD program in Computer Science, Machine Learning, Artificial Intelligence, Data Science, or a related discipline.
Strong foundation in machine learning, deep learning, and statistical modeling.
Proficiency in Python and experience with ML libraries such as PyTorch, TensorFlow, or Scikit-learn.
Understanding of data processing tools (e.g., pandas, NumPy, Spark, or SQL).
Familiarity with data visualization tools (Tableau, Power BI, or similar).
Strong analytical, problem-solving, and research skills.
Excellent written and verbal communication skills, with the ability to convey technical insights clearly.
Hands-on experience with large-scale data pipelines, cloud AI platforms (AWS, Azure, GCP), or distributed computing frameworks.
Experience with GenAI, Explainable AI (XAI) or NLP/NLU model fine-tuning and Retrieval-Augmented Generation (RAG) frameworks.
Familiarity with containerization and CI/CD tools (Docker, GitHub Actions, Jenkins).
Experience integrating ML models into production software systems.
Prior experience in data analytics, research, or applied AI/ML development.
Exposure to network optimization, telecommunications, or edge AI applications.
What happens once you apply?
Click Here to find all you need to know about what our typical hiring process looks like.
Ericsson uses a merit-based hiring approach that values people with different experiences, perspectives and skillsets. We truly believe this approach drives innovation, which is essential for our future growth. We encourage people from all backgrounds to apply and realize their full potential as part of our Ericsson team. Ericsson is proud to be an Equal Opportunity employer, learn more.
If you need assistance or to request an accommodation due to a disability, please contact Ericsson at hr.direct.americas@ericsson.com.
DISCLAIMER: The above statements are intended to describe the general nature and level of work being performed by employees in this position. They are not an exhaustive list of all responsibilities, duties and skills required for this position, and you may be required to perform additional job tasks as assigned.
Primary country and city: Canada (CA) \|\| Ottawa
Job details: Developer
Compensation and Benefits at Ericsson
At Ericsson, we know that our people are the key to our success. We offer a competitive package to help with your individual needs and goals.
Your Pay
The salary offered is dependent on various factors including, but not limited to, location, and the candidate’s combination of job-related knowledge, qualifications, skills, education, training, and experience.