Junior Software Development Engineer Intern

Complete an internship project at SOPHiA GENETICS whose mission is to build the future of AI-assisted medicine, joining the Technology, Data Science Engineering Team as a Junior Software Development Engineer Intern. 

Your mission: 

We are seeking an intern to work on a project aimed at significantly enhancing the performance and efficiency of genomic analysis pipelines. This role involves building a unified monitoring dashboard to optimize the cost, technical performance, and turnaround time (TAT) of workflow executions on SOPHiA’s genomic analysis executor. Using tools such as Grafana or New Relic, you will play a critical role in driving improvements in pipeline execution, ultimately reducing costs and improving the speed and accuracy of genomic data processing. 

You will work on a project focused on streamlining the execution of complex bioinformatics workflows. The unified dashboard will provide real-time insights into cost and resource usage, technical performance (e.g., compute and memory), and the analytical performance (e.g., accuracy, precision) of the genomic pipelines. By improving these aspects, this project will directly contribute to reducing the turnaround time and cost of genomic analysis, making it more efficient and scalable. 

You will be involved in: 

• Designing, building, and maintaining a multi-faceted monitoring dashboard (cost, technical performance, and analytical metrics) using Grafana or New Relic. 

• Integrating cloud cost data, technical infrastructure metrics (CPU, memory), and analytical results into a unified tool. 

• Monitoring and optimizing resource usage during critical stages of genomic analysis. 

• Implementing performance monitoring and tracing for key pipeline tasks using Prometheus, OpenTelemetry, and Jaeger. 

• Collaborating with bioinformatics and cloud infrastructure teams to ensure that the workflows are performant, cost-effective, and scalable. 

Requirements

Technical competencies: 

• Knowledge of monitoring tools (Grafana, New Relic) and cloud environments (AWS, Azure, or GCP). 

• Familiarity with bioinformatics workflows and genomic data processing is a strong plus. 

• Understanding of Prometheus, OpenTelemetry, and performance monitoring. 

• Basic knowledge of microservices and distributed cloud infrastructure. 

• Interest in cloud-based optimization of bioinformatics pipelines. 

• Strong communication skills in English. 

Social skills:  

• Collaborator: you will work closely with bioinformatics and cloud infrastructure teams, gathering requirements and feedback to improve the performance and cost-efficiency of genomic workflows. 

• Communication skills: ability to translate complex technical concepts for both technical and non-technical team members and collaborate across departments. 

Benefits

What you will learn: 

As an intern, you will gain hands-on experience in optimizing genomic analysis pipelines. You will learn how to design and implement monitoring solutions using tools like Grafana or New Relic, and you will gain a deeper understanding of bioinformatics workflows and cloud infrastructure management. This project will give you valuable insights into improving the efficiency, scalability, and cost-effectiveness of large-scale genomic analysis. 

Application process 

Apply now with your CV and any supporting information. 

Suitably qualified candidates will be invited through an interview and screening process where you will speak with members of our Talent Acquisition Team, the hiring leader, alongside key colleagues, and stakeholders from across the business. 

All resumes should be in English for a successful review! 

 SOPHiA GENETICS: 

We believe there is a smarter, more data-driven way to make decisions in healthcare and our AI SaaS Platform enables that. You will have direct input into our mission to radically improve the outcomes for Cancer & Rare Disease patients globally. Enable our customers to push industry boundaries, as we pioneer into newly discovered fields and combine complex, multi-modal data for the first time! 

For more information, visit our website: https://www.sophiagenetics.com.