We are seeking a capable and self-driven Junior Machine Learning Engineer with 3-4 years of experience and hands-on expertise in building and deploying production-grade ML systems. This role focuses on designing and maintaining scalable ML pipelines and workflows rather than only building isolated models.

Key Responsibilities

Build and manage end-to-end ML pipelines (data prep, training, deployment, monitoring)
Deploy ML systems on cloud platforms (AWS/Azure) using Docker/ Kubernetes
Create reusable components for multiple workflows
Write clean, production-ready Python code
Implement GPU processing for ML workflows
Monitor and improve deployed models in production

Required Experience & Skills

Skills:

Strong hands-on Python skills with ML libraries (scikit-learn, pandas, NumPy, PyTorch, TensorFlow)
Proven experience in building full ML pipelines (not just notebooks)
Solid understanding of production pipeline design patterns
Experience with Computer Vision and NLP pipeline development
Knowledge of production best practices: versioning, automation, monitoring

Good-to-Have Skills:

Hands-on AWS/Azure experience for ML workloads
Familiarity with containers and Docker
GPU pipelines setup for ML deployments
Experience with testing frameworks for ML pipelines and APIs
Knowledge of multi-tenant ML platform architecture

Why Join tracebloc

Impactful Work: Shape how data scientists and AI teams collaborate securely
Growth Opportunities: Work with an experienced leadership team and cutting-edge tech
Competitive Compensation: Upper-market salary, performance incentives, and equity options
Vibrant Culture: Flexible working, diverse team, and creative autonomy in central Berlin

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