Join our Team

At this time, Ericsson Canada Inc. does not provide immigration assistance/sponsorship now or in the future for this position.

About This Opportunity

Ericsson is accelerating the use of AI and GenAI across our products and how we build them. In this role, you will help shape how engineers and product teams use data, AI, and agentic workflows every day—driving better decisions, smarter automation, and faster innovation across our RAN management and software portfolio.

You will join a growing data and AI group that is building production-grade data products and AI systems end-to-end, from raw telemetry and platform data to deployed AI agents and ML services used by internal users worldwide. Our data platform ingests large-scale RAN and software lifecycle data and provides the foundation for analytics, automation, and AI/ML.

As a Data Scientist, you will be a senior individual contributor working closely with a lead engineer. You will focus on designing and implementing agentic AI solutions, robust data pipelines, and solid data management and governance practices that enable scalable, reliable, and compliant use of data across our organization.

What You Will Do

Design and build agentic AI workflows and systems that orchestrate tools, data, and models to improve engineering, operations, and product development processes Develop and deploy production-grade ML and GenAI solutions (including LLM-based agents) that support use cases such as developer assistance, intelligent automation, monitoring, and decision support Collaborate with data platform and engineering teams to design, implement, and operate reliable data pipelines and features for AI/ML use cases (batch and, where relevant, streaming) Contribute to the design and evolution of our data platform, including data models, feature stores, metadata, and observability for AI/ML workloads Apply LLMs and GenAI techniques (prompt engineering, fine-tuning, Retrieval-Augmented Generation) to build practical, secure, and robust AI applications Implement and follow MLOps best practices, including experiment tracking, model versioning, automated deployment, monitoring, and A/B testing Work closely with data management and governance stakeholders to ensure that data used by AI/ML and agentic workflows meets quality, lineage, privacy, and access control requirements Analyze complex datasets to derive actionable insights that inform platform evolution, process optimization, and AI/ML roadmap priorities Document solutions, patterns, and best practices so other teams can build on your work and adopt the data platform and AI capabilities effectively Collaborate with cross-functional partners (engineering, product, operations, security, governance) to understand needs, frame problems, and translate them into robust data and AI solutions

The skills you will bring

Proven experience as a Data Scientist or similar role, delivering production ML or GenAI solutions end-to-end (from data to deployed systems), ideally in a complex platform or product environment Strong hands-on skills with Python for data science and ML, and solid proficiency with SQL for working with large datasets and analytical queries Practical experience with LLMs and GenAI applications, including some of the following: Prompt engineering and tool-augmented agents Fine-tuning or adaptation of foundation models Retrieval-Augmented Generation (RAG) Experience building or operating agentic AI systems (e.g., multi-step tool-using agents, workflow orchestration for LLMs, conversational task assistants) Solid understanding of data pipelines and data platform concepts, for example: Building and operating ETL/ELT pipelines for large-scale structured and semi-structured data Working with modern data platforms (e.g., Spark, Trino/Presto, data lakehouse formats such as Iceberg/Delta/Parquet, or equivalent technologies) Designing data models and features to support AI/ML workloads Familiarity with MLOps practices, including: Experiment tracking and model versioning CI/CD for ML, automated training and deployment Online/offline evaluation, monitoring, and alerting for models and AI agents Experience with data management and governance principles, such as: Data quality, lineage, and cataloging Access controls, privacy, and compliance considerations Working with governance frameworks and stakeholders to implement policies in practice Strong analytical and problem-solving skills, with the ability to translate ambiguous or open-ended problems into clear, data- and AI-driven solutions Clear communication skills: able to explain complex technical concepts and trade-offs in simple terms to engineering, product, and business stakeholders A collaborative, proactive mindset and comfort working under a lead engineer while driving your own workstreams independently Nice To Have

Experience with software engineering practices (version control, code review, testing) and modern development stacks (e.g., containerization with Docker/Kubernetes, cloud-native architectures) Exposure to streaming data technologies (e.g., Kafka, Spark Streaming, Flink) Experience with metrics, telemetry, or CI/CD data related to software development processes Familiarity with telecom, RAN, or network management domains Master’s degree in Data Science, Computer Science, Statistics, or a related field, or equivalent practical experience

Why join Ericsson?

At Ericsson, you´ll have an outstanding opportunity. The chance to use your skills and imagination to push the boundaries of what´s possible. To build solutions never seen before to some of the world’s toughest problems. You´ll be challenged, but you won’t be alone. You´ll be joining a team of diverse innovators, all driven to go beyond the status quo to craft what comes next.

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 (Country/ City)

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.

The salary range for this position is

Ottawa: $101,500CAD- $ 133,350CAD

Short-Term Variable Compensation Plan: Your pay also includes the opportunity for an annual bonus. Actual bonus payouts are based on performance of the business against the unit’s objectives, individual performance, and the individual bonus target. Certain eligibility and pro-ration rules apply.

Your Time

Your work-life balance is important to us. New employees are provided a minimum of 18 days of accrued vacation, at least 3personal days, minimum 10 holidays, 1 volunteer day, and sick days. Please note paid time off is pro-rated based on the employee’s start date. Furthermore, Ericsson provides up to 10 weeks of paid maternity leave and 6 weeks of parental or adoption leave at 100% of pay.

Additional Benefits

Ericsson offers many other company-paid benefits such as financial wellness programs, educational assistance, matching gifts, wellness account, and recognition programs.