Senior Full-Stack Software Machine Learning Engineer

SOPHiA GENETICS (Vaud, Switzerland) Follow 3 hours ago

Are you an experienced full-stack software engineer with a passion for building impactful digital healthcare solutions? Join our team to develop and deliver web modules and microservices for a globally distributed platform that connects hospitals and labs. You’ll focus on genomics interpretation, data processing, and analysis, contributing to our SaaS platform that transforms how complex healthcare data is shared and utilized. You also bring machine learning engineering experience, including designing RAG pipelines and evaluating LLM-based systems.

If this sounds like you and you are driven by purpose, join the SOPHiA GENETICS Software Engineering team as our new Senior Full-Stack Software Machine Learning Engineer , and enable us to make a positive impact on the outcomes for cancer and rare disease patients worldwide.

This is a hybrid opportunity, requiring 3 days onsite at our corporate office in either Bidart, FR, Rolle, CH or Boston, MA. Please ensure that all CV/Resumes are submitted in English as we are an international company that uses English as our language of business.

Responsibilities

End-to-End Software Development & Delivery

Develop and optimize web-based services and components, leveraging modern frameworks (React, Next.js, Node.js) and robust backend technologies (Java, microservices) to deliver seamless user experiences.
Own and drive the full lifecycle of complex, high-performance software systems - from design and implementation to testing, deployment, and maintenance - ensuring reliability and scalability.
Enhance system performance through database optimization (MySQL, MariaDB, DuckDB) and efficient query design, ensuring data integrity and fast processing.
Leverage AI and modern tools to enhance SDLC, observability, monitoring, and system intelligence, driving data-driven decision-making.
Design, integrate and evolve machine learning components into a production environment, including RAG pipelines for knowledge retrieval and systematic ML model evaluation frameworks.

Technical Leadership & Collaboration

Orchestrate cross-functional projects by collaborating with Product, QA, Architecture, and other teams to design interoperable systems and deliver high-impact features.
Lead code reviews and mentor junior engineers, fostering a culture of quality, innovation, and continuous improvement.
Resolve complex technical issues with efficiency, minimizing downtime and ensuring smooth operations.

Operational Excellence & Process Improvement

Streamline SDLC processes, integrating Agile, CI/CD, and DevOps tools (Docker, Kubernetes, GitLab) to accelerate delivery and improve workflow automation.
Collaborate with stakeholders (PMO, Product, QA, Architecture) to align technical execution with product vision and user needs.

Business Understanding

Bridge technical execution with business goals by deeply understanding the genomics and digital healthcare domain, ensuring solutions align with user needs and regulatory requirements.
Advocate for user-centric improvements by reviewing designs against ease of use and suggesting enhancements to product stakeholders based on hands-on experience.

Requirements

5-7 years’ experience in the web development field
Bachelor’s degree in Computer Science or Engineering or equivalent professional experience
Demonstrated experience in developing reliable web-based services and a firm grasp on the underlying challenges of releasing web components to production
Solid proficiency of front-end framework: React, Next.js, Node.js, JSX
Proficiency in Java for back-end development
Solid understanding of backend technologies and microservices architecture
Experience with databases like MySQL, MariaDB, and DuckDB, and database design and query optimization
Experience with AI use in SDLC
Experience with machine learning engineering in a production environment, including building and evaluating RAG pipelines, LLM evaluation methodologies and general lifecycle management
Familiarity with Linux environments and GitLab for version control and CI/CD pipelines
Good knowledge of software engineering best‑practices, Agile, CI/CD, testing frameworks, TDD, BDD
Familiarity with monitoring and observability tools like Grafana and Loki is a plus
Knowledge of GraphQL is a plus
Knowledge of modern DevOps tools is a plus
Experience with containerization (Docker) and orchestration (Kubernetes) technologies is a plus
Experience in the domain of genomics and digital healthcare is a plus

Benefits