Machine Learning Engineer for Scalable Model Deployment
1 semana atrás
We are seeking a skilled Machine Learning Engineer to design and deploy scalable systems to train, monitor, and expose machine learning models in production.
Key Responsibilities:- Owning the system architecture to train, retrain, develop, monitor, and expose machine learning models;
- Designing and maintaining scalable infrastructure for ML pipelines and APIs;
- Implementing CI/CD pipelines for ML model deployment, updates, and continuous monitoring;
- Collaborating closely with data scientists and cross-functional teams to ensure seamless integration of ML models into production;
- Ensuring compliance with security and privacy requirements, particularly in a financial context;
- Troubleshooting and optimizing ML production systems, ensuring performance, reliability, and scalability;
- Sharing knowledge, mentoring, and supporting team members in best practices for MLOps and API development.
To succeed in this role, you must have experience in MLOps, DevOps or related roles, as well as strong experience with cloud platforms, containerization tools, and ML frameworks. You should also have proficiency in Python and experience with CI/CD tools, data pipelines, and monitoring solutions.
In addition to your technical expertise, excellent communication and collaboration skills are essential for success in this position.
We offer a competitive compensation package and opportunities for growth and professional development.
This is an exciting opportunity to join our team and contribute to the development of cutting-edge machine learning solutions.
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