Overview
As a Software Engineer in the AI Engineering team, you will develop, deploy and maintain applications, AI/ML services (e.g. LLM services) and data pipelines that support production
Full job description
As a Software Engineer in the AI Engineering team, you will develop, deploy and maintain applications, AI/ML services (e.g. LLM services) and data pipelines that support production AI services at scale as well as provide development tooling for our data scientists and product engineers. You will be responsible for designing and developing them in a performant, reliable and maintainable manner while leveraging pragmatic unit, integration and performance testing.
Influence the roadmap and development of applications and pipelines
Deploy and maintain performant AI/ML services
Design, develop, deploy and maintain high-quality code following engineering and testing best practices
Work with data scientists, product engineers and users to enable new AI capabilities
Background in quantitative field (e.g. Engineering, Computer Science, Mathematics, Physics etc) and 3 or more years of relevant work experience
Proficiency in Python, Java or similar programming languages
Practical experience with databases such as RDBMS, NoSQL, vector scores
Experience in software deployment, including with tools for CI/CD and other deployment processes
Familiarity with containerization and container orchestration platforms (e.g. Docker, Kubernetes)
Good understanding of domain-driven design, microservice patterns and service-oriented architectures
Technical leadership experience such as mentoring other engineers or driving collaborations with other engineering teams
Experience with Python web frameworks (e.g. Flask, FastAPI)
Experience in designing and maintaining data pipelines with high reliability/throughput requirements
Experience with deploying and maintaining AI/ML services (e.g. deploying LLM services via vLLM) for high reliability/throughput use cases
Tips for this job
Practical Job and Scholarship guidance. These tips do not replace official rules or create new eligibility requirements.
- Tailor the CV and application to the responsibilities and required skills stated on the official employer page.
- Use concrete evidence of relevant work, projects and measurable results rather than generic claims.
- Confirm location, work authorization, remote restrictions and sponsorship terms before applying.
- Apply through the original employer or official recruitment destination shown on this page.
Verification notes
laptop-ats-crawler v2
Job and Scholarship is the discovery and verification layer. Confirm eligibility, dates, salary/funding and application instructions on the original source before submitting anything.
Csit (lever) ↗Browse current Job and Scholarship listings from Csit (lever) →
