Senior Machine Learning Engineer

Darum lohnt es sich

Proficient in Python and experienced in mentoring teams while implementing best software engineering practices. • 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.

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