AI Engineer – PyTorch & MLOps

Twine; Schweiz; Vor Ort; CHF 120.000 - 180.000; Vollzeit

Zusammenfassung

Twine in Switzerland seeks an experienced AI/ML Engineer to design, train, deploy and optimize deep learning models for production. You will build scalable data pipelines, integrate models into cloud services, and monitor performance.

Collaborate with software, product and data teams to deliver end-to-end AI solutions and implement MLOps for CI/CD. Responsibilities include troubleshooting, ensuring reliability and accelerating deployment speed for mission-critical applications in a fast-paced

Qualifikationen

• 3+ years of experience building and deploying ML models in production.
• Proficiency in Python and at least one of C++ or Java.
• Hands-on with PyTorch, TensorFlow, or Scikit-learn.
• Strong Docker, Kubernetes and cloud platform experience (AWS or GCP).
• Experience designing data pipelines and APIs.
• Knowledge of MLOps, CI/CD and model monitoring.
• Advanced SQL skills and excellent English communication.

Aufgaben

• Design, train, deploy and optimize DL models for production.
• Build scalable data processing pipelines for training and inference.
• Integrate ML models into cloud services and APIs.
• Monitor model performance and troubleshoot in production.
• Collaborate with software, product and data teams on end-to-end AI solutions.
• Apply MLOps best practices for CI/CD in production environments.
• Improve speed, reliability and scalability of mission-critical apps.

Kenntnisse

Machine learning in prod

Python

C++ or Java

PyTorch / TensorFlow / Scikit-learn

Docker / Kubernetes

Cloud platforms (AWS or GCP)

SQL

English communication

Jobbeschreibung

Join a dynamic team focused on scaling advanced AI solutions for production environments. This role centers on building, training, deploying, and optimizing deep learning models, as well as developing robust data processing pipelines. You will collaborate closely with software, product, and data teams to integrate models into cloud-based services, ensuring seamless deployment and operational excellence. The position also involves monitoring model performance, troubleshooting issues, and driving improvements in speed and reliability for mission-critical applications.

Deliverables

• Design, develop, and deploy deep learning models using PyTorch and related frameworks
• Build and maintain scalable data processing pipelines for model training and inference
• Integrate machine learning models into cloud services (AWS or GCP) and APIs
• Monitor, evaluate, and optimize model performance in production environments
• Collaborate with cross-functional teams to deliver end-to-end AI solutions
• Implement MLOps best practices for continuous integration and deployment
• Troubleshoot and resolve issues related to model reliability and scalability

Requirements

• Minimum 3 years of experience building and deploying machine learning models in production
• Proficiency in Python and at least one of C++ or Java
• Hands-on experience with PyTorch, TensorFlow, or Scikit-learn
• Strong background in Docker, Kubernetes, and cloud platforms (AWS or GCP)
• Experience designing and maintaining data pipelines and APIs
• Solid understanding of MLOps, CI/CD, and model monitoring
• Advanced SQL skills for data manipulation and analysis
• Excellent English communication skills for collaboration with international teams
• Ability to work independently and deliver results in a fast-paced environment

About Twine

Twine is a leading freelance marketplace connecting top freelancers, consultants, and contractors with companies needing creative and tech expertise. Trusted by Fortune 500 companies and innovative startups alike, Twine enables companies to scale their teams globally.

Our Mission

Twine's mission is to empower creators and businesses to thrive in an AI-driven, freelance-first world.