Software Engineer

Vyoma

Posted 2mo ago

The employer’s full description could not be read from their board. This is a summary of the posting — follow the apply link for the original.

Design, develop, and maintain high-quality, high-performance software pipelines that process payload image data and expose high-level information to downstream systems.
Own software quality end-to-end: write well-structured, testable code, define validation plans, and ensure full unit and integration test coverage before merging.
Drive system design decisions — propose, evaluate, and implement architectural patterns and abstractions that keep our codebase scalable and maintainable as the system grows.
Review code thoughtfully and thoroughly, raising the engineering bar across the team and mentoring colleagues on software best practices.
Identify and implement improvements in performance, reliability, and observability — from algorithmic optimisation to parallelisation strategies and deployment workflows.
Collaborate with domain experts in computer vision and numerical algorithms, translating research-grade ideas into production-ready software.
Proactively identify problems and propose solutions before they become blockers — we value engineers who take ownership.

5+ years of professional software development experience in industry, with a proven track record of shipping and maintaining production systems.
Strong Python skills: you are comfortable writing idiomatic, performant, and well-tested Python.
Solid software engineering fundamentals: design patterns, clean architecture, separation of concerns, and a genuine care for code maintainability.
Strong understanding of software testing methodologies, including unit, integration, and regression testing.
Experience with CI/CD pipelines and automated testing frameworks (e.g., GitLab CI, GitHub Actions, or Jenkins).
Ability to work both independently and collaboratively in a multidisciplinary team.
Valid working permit in Germany (or the EU)

Experience with cloud infrastructure and containerisation (e.g., Docker, Kubernetes, AWS, or equivalent).
Familiarity with databases, data pipelines, and deployment workflows in production environments.
Experience with parallel and distributed computing patterns.
Mathematical or scientific background: familiarity with numerical methods, signal processing, optimisation, or linear algebra, and hands-on experience with scientific Python libraries (e.g., NumPy, SciPy, OpenCV) is a strong plus and will help you thrive working alongside our algorithm experts.

Skills