Responsibilities
- Model Development: Design, train, and optimize machine learning models for production use.
- Architecture & Scalability: Build robust, scalable ML pipelines and data processing systems.
- Research & Innovation: Stay ahead of emerging AI/ML trends and integrate cutting-edge techniques.
- Collaboration: Work closely with data scientists, software engineers, and product managers to align ML solutions with business goals.
- Mentorship: Guide and review the work of junior ML engineers and data scientists.
- Deployment & Monitoring: Implement CI/CD for ML models, ensuring performance, reliability, and fairness.
Basic qualifications
- Strong proficiency in Python, TensorFlow, PyTorch, scikit-learn.
- Experience with cloud platforms (AWS, GCP, Azure) and MLOps tools.
- Deep understanding of NLP, Computer Vision, or Recommendation Systems.
- Strong grasp of data structures, algorithms, and distributed computing.
- Soft Skills: Excellent problem-solving, leadership, and communication abilities.
Benefits
- Direct cooperation with the already successful, long-term, and growing project.
- Flexible work arrangements.
- Collaborative and supportive team culture.
- Truly competitive salary.
- Help and support from our caring HR team.
Tags & focus areas
Used for matching and alerts on DevFound Machine Learning Data Science Computer Vision Mlops Pytorch Tensorflow Ai