Senior AI/MLOps Engineer
Tasks
- Collaborate with data science on model optimization
- Communicate machine learning concepts to stakeholders
- Conduct code reviews and establish best practices
- Deploy machine learning models to production
- Design and oversee machine learning pipelines
- Drive development of scalable reliable machine learning systems
- Implement data governance risk management compliance
- Lead integration of machine learning tools and technologies
- Lead machine learning infrastructure strategy
- Lead model experimentation and evaluation
- Manage real time and batch inference systems
- Mentor machine learning engineers
- Optimize models for production environments
Perks/Benefits
- Coffee
- Corporate events
- Flexible working hours
- Fresh fruit
- Home office option
- Hybrid work
- Internal trainings
- International conference opportunities
- Loyalty bonus
- Meal allowance
- Multisport card
- Paid certifications
- Paid holiday
- Referral bonus
- Remote work options
- Sick days
- Soft-skills training
- Team building
- Technical training
- Weekly office breakfast
Skills/Tech-stack
A/B | A/B Testing | AWS | Apache Airflow | Apache Kafka | B testing | Dagster | DevOps | Docker | Experiment tracking | Generative AI | Grad-CAM | Kubernetes | Language Models | Large Language Models | MLOps | MLflow | Machine Learning | Model Explainability | Model Governance | Model Risk Management | Model risk | NLP | Python | Risk Management | SHAP | SQL | Stream processing
Education
N/A
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