Onebridge, a Marlabs Company, is a global AI and Data Analytics Consulting Firm that empowers organizations worldwide to drive better outcomes through data and technology. Since 2005, we have partnered with some of the largest healthcare, life sciences, financial services, and government entities across the globe. We have an exciting opportunity for a highly skilled Software Engineer (Python) to join our innovative and dynamic team.
Software Engineer (Python) |
About You
As a Software Engineer (Python), you are responsible for building clean, scalable, and reliable solutions that support data-driven and AI‑enabled environments. You enjoy developing well‑tested Python applications and working within cloud-native ecosystems. You collaborate effectively across engineering, data, and scientific teams, turning complex requirements into production-ready solutions. You value best practices such as documentation, testing, automation, and continuous improvement. You’re motivated by work that drives innovation and accelerates scientific and analytical outcomes.
Software Engineer (Python) |
Day-to-Day
- Develop and maintain clean, well-structured Python code with strong documentation and unit testing.
- Deploy, troubleshoot, and optimize applications in cloud environments using Docker and Kubernetes.
- Support and enhance CI/CD pipelines, improve automation, and deployment workflows.
- Collaborate with cross-functional teams, including scientists, data engineers, and ML engineers, to operationalize AI and analytical tools.
- Participate in code reviews, design discussions, and architectural improvements.
- Ensure reliability, performance, and scalability across production systems and services.
Software Engineer (Python) | Skills & Experience
- 5+ years of professional software engineering experience, with a proven track record of delivering production-quality applications in Python.
- Deep hands-on experience working with Docker, Kubernetes, and cloud platforms (with a strong preference for AWS).
- Strong proficiency in Git, version control workflows, unit testing frameworks, and modern CI/CD tooling.
- Demonstrated ability to debug, troubleshoot, and resolve complex software, infrastructure, and deployment issues in production environments.
- Experience collaborating with multidisciplinary teams to deploy or support AI, machine learning, or scientific applications in real-world settings.
- Familiarity with large-scale, cloud-native infrastructures and the ability to apply best practices around reliability, observability, and system performance.
