Computer Vision Engineer, Applied ML

Description

In this role, you will operate at the intersection of applied machine learning and software engineering, building and deploying computer vision systems in real-world environments. You will design, train, evaluate, and debug machine learning models, taking solutions from early prototypes through to robust, production-ready deployments. A part of your work will involve curating high-quality datasets to support model performance and continuous improvement. You will build and apply state-of-the-art vision models, staying up to date with the latest advancements and integrating new approaches where they add value.

First and foremost, we believe in curious people who are eager to learn and grow. If you’re passionate about cutting-edge tech and driving major impact in manufacturing, we want to hear from you. Please also reach out if you don’t check all the points mentioned here.

Responsibilities

• Design, train, evaluate, and debug machine learning models
• Build and deploy computer vision systems
• Curation of high-quality datasets to support model performance and continuous improvement
• Build and apply state-of-the-art vision models

Qualifications

Must-Haves:

• Strong technical foundation in computer science with focus on computer vision (CV) and machine learning (ML), whether gained through formal education or substantial real-world experience
• Solid understanding of core ML and CV concepts, including training dynamics, generalization, bias-variance tradeoffs, evaluation methodology, and common failure modes
• Hands-on model training experience: able to set up training loops, debug convergence, tune hyperparameters, and evaluate properly on real CV tasks
• Shipped a model or CV pipeline in a production or near-production environment with real users beyond a research or internal project.
• Excellent communication skills in spoken and written English
• Strong motivation to work in a dynamic and fast-paced environment

Bonus:

• Expertise in visual quality, defect or anomaly detection
• Experience in model deployment, such as ONNX, and MLOps basics
• Experience in visualization of model internals and explainability

Benefits

• Performance-based career & growth paths
• On-site work with significant scope for flexible schedules
• Competitive compensation including stock options giving you a stake in Ethon's long-term success
• Vacation bonus if you take two consecutive weeks of vacation
• Flexible parental leave
• Learning budget for courses, conferences, and coaching