Senior Machine Learning Engineer

Jobtailor; Deutschland; Vor Ort; EUR 90.000 - 120.000; Vollzeit

Zusammenfassung

Jobtailor seeks an experienced ML Engineer (MLOps) to drive production ML systems in a German environment. You will design scalable pipelines, optimize CI/CD with GitLab, and implement MLflow tracking.

The role requires strong Python and AWS SageMaker experience, mentoring teammates, and clear communication with stakeholders to align on roadmaps and system design.

Qualifikationen

• Degree in CS or related field (Bachelor's).
• Master's/PhD in CS/AI/ML preferred.
• Strong Python and ML ecosystem knowledge.

Aufgaben

• Drive and improve MLOps practices across the ML environment.
• Build and optimize CI/CD pipelines using GitLab.
• Implement ML experiment tracking and model management with MLflow.
• Productionize and deploy ML models using AWS SageMaker.
• Design and maintain scalable ML and data pipelines.
• Develop and maintain Python-based ML and data infrastructure.
• Implement monitoring and observability for ML systems.
• Provide technical guidance and mentor Data Scientists, Data Engineers, and MLOps Engineers.
• Apply software engineering best practices, including testing and documentation.
• Collaborate with Product Managers, Data Scientists, Engineers, and stakeholders.
• Evaluate and introduce new technologies to improve ML capabilities.

Kenntnisse

MLOps

Python

Mentoring

Documentation

Stakeholder mgmt

Communication

Ausbildung

Bachelor's in CS

Master's/PhD in CS/AI/ML

Tools

AWS

GitLab

MLflow

Prometheus

Grafana

Evidently AI

Jobbeschreibung

• Drive and improve MLOps practices across the ML environment
• Build and optimize CI/CD pipelines using GitLab
• Implement ML experiment tracking and model management with MLflow
• Productionize and deploy machine learning models using AWS SageMaker
• Design and maintain scalable ML and data pipelines
• Develop and maintain Python-based ML and data infrastructure
• Implement monitoring and observability for ML systems
• Provide technical guidance and mentor Data Scientists, Data Engineers, and MLOps Engineers
• Apply software engineering best practices, including testing, documentation, and system design
• Collaborate with Product Managers, Data Scientists, Engineers, and business stakeholders
• Evaluate and introduce new technologies to improve ML capabilities

Requirements

• 5+ years of professional experience in Machine Learning Engineering
• Strong experience deploying and maintaining production ML systems
• Expert-level Python skills and knowledge of the data science ecosystem
• Hands-on experience with AWS, preferably AWS SageMaker
• Strong knowledge of MLOps practices and lifecycle
• Practical experience with MLflow
• Experience with GitLab CI/CD
• Experience with at least one major deep learning framework, e.g. PyTorch or TensorFlow
• Experience designing and building scalable ML and data pipelines
• Experience with ML system monitoring and observability
• Ability to design, document, and communicate complex technical architectures
• Experience mentoring and providing technical guidance to other engineers and data scientists
• Strong communication and stakeholder management skills
• Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience
• Preferred: Master's or PhD in Computer Science, AI, or Machine Learning
• Preferred: Experience with Prometheus, Grafana, or Evidently AI
• Preferred: Experience working with large-scale recommender systems
• Preferred: Strong understanding of software engineering and system design principles

Core Competencies

Demonstrates expertise in Machine Learning Engineering with a strong focus on MLOps practices, CI/CD pipeline optimization, and productionizing ML models using AWS SageMaker. Proficient in Python and experienced in mentoring teams while implementing best software engineering practices.

Highest-signal resume keywords

• Machine Learning Engineering
• AWS SageMaker
• Python Programming
• MLOps Practices
• CI/CD Pipeline Development

ATS Optimization Keywords

Hard Skills

• Machine Learning Engineering
• Python Programming
• MLOps Practices
• CI/CD Pipeline Development
• MLflow
• Deep Learning Frameworks
• Monitoring and Observability
• Data Pipeline Design
• Technical Documentation
• System Design

Soft Skills

• Technical Guidance
• Mentoring
• Communication
• Stakeholder Management

Certifications & Qualifications

• Bachelor's Degree in Computer Science
• Master's or PhD in Computer Science, AI, or Machine Learning

Industry Keywords

• MLOps
• Machine Learning
• Data Science Ecosystem
• Recommender Systems

Tools & Technologies

• AWS
• GitLab
• MLflow
• Prometheus
• Grafana
• Evidently AI