Data Science Engineer (AI)

TL;DR

Data Science Engineer (AI/ML): Building AI-native systems for real-time supply chain risk visibility with an accent on NLP and ML model production. Focus on transforming complex datasets into actionable intelligence and deploying scalable ML models using Torch and TensorFlow.

Location: Hybrid in Vienna

Salary: Minimum EUR 45,738 gross annually

Company

AI-native company providing real-time supply chain risk visibility for major enterprises like BMW Group, Hilti, and Lufthansa.

What you will do

• Utilize NLP to extract meaning and actionable intelligence from diverse, complex datasets.
• Develop, fine-tune, and deploy machine learning models using Torch and TensorFlow.
• Transform cutting-edge research algorithms into production-ready, scalable solutions.
• Monitor, enhance, and continuously improve model performance and accuracy.
• Identify and integrate new data sources to enrich the intelligence universe.
• Collaborate with cross-functional teams to solve business challenges with data-driven solutions.

Requirements

• Bachelor’s degree (or higher) in Computer Science, Statistics, Mathematics or related fields.
• 3+ years of experience in developing, deploying, and scaling ML models to production.
• Proficiency in NLP and tools like Torch or TensorFlow.
• Strong experience working with Python and Scala.
• Knowledge of SQL and relational databases.
• Ability to work in a hybrid setup in Vienna.

Nice to have

• Master’s degree in a related field.
• Understanding of cloud-based services (GCP or AWS).
• Knowledge of NoSQL database systems.
• Knowledge of agile software development techniques.
• Experience with agent engineering and AI tools like Cursor or Claude.

Culture & Benefits

• AI-native workflow using tools like Claude and Cursor to eliminate repetitive tasks.
• High degree of ownership and trust to execute tasks independently.
• Flexible hours and hybrid working model.
• Comprehensive health support, including mental health and regular check-ups.
• Perks: birthday off, device of choice, and the ability to work from anywhere up to 8 weeks a year.