AI/ML Software Engineer - Research Workflows (Zurich) Visa

Clera; Zürich; On-site; CHF 120,000 - 170,000; Full time

Benefits offered by this job

Equity

Visa sponsorship

Competitive compensation

Job summary

Clera in Zürich, Switzerland, is seeking an experienced software engineer to join our AI/ML engineering team. You will build user-facing interfaces and backend services to support research workflows, with a focus on reliability and performance.

You will collaborate with researchers to design APIs, work with PostgreSQL data models, and connect applications to data pipelines, while maintaining code quality through testing and reviews.

Qualifications

• 3+ years building and maintaining applications used by others.
• 5–10+ years preferred.
• Strong TypeScript and React skills, or Python with FastAPI.
• Experience designing APIs and working with SQL and PostgreSQL.
• A practical approach to testing, debugging, and incorporating user feedback.
• Experience with annotation tools or large dataset exploration is valuable.

Responsibilities

• Build interfaces for creating tasks, reviewing files and video, inspecting agent actions, and comparing experimental results.
• Develop APIs and PostgreSQL data models for tasks, reviews, files, and experiments.
• Connect applications to data pipelines and file storage with input validation, permission controls, and clear error handling.
• Work with researchers and domain experts to improve workflows, investigate bugs, and maintain performance as datasets grow.

Skills

TypeScript

React

Python

FastAPI

API design

SQL

PostgreSQL

Collaborative problem solving

Tools

PostgreSQL

AWS S3

Data pipelines

Job description

Clera in Zürich, Switzerland, is seeking an experienced software engineer to join our AI/ML engineering team. You will build user-facing interfaces and backend services to support research workflows, with a focus on reliability and performance.

You will collaborate with researchers to design APIs, work with PostgreSQL data models, and connect applications to data pipelines, while maintaining code quality through testing and reviews.