Senior Machine Learning Engineer

Description

Job Summary: We are seeking a Senior Machine Learning Engineer to work at the intersection of machine learning, cloud technologies, and system architecture, developing strategic AI solutions. Key Highlights: 1. Strategic involvement in AI product development. 2. Focus on best practices in MLOps, scalability, and security. 3. Collaboration with cross-disciplinary teams. Description: * Bachelor's degree in Computer Science, Statistics, Engineering, Mathematics, Physics, or related fields; * Proficiency in Python and SQL; * Knowledge of cloud computing platforms (AWS, Azure, or GCP); * Familiarity with RESTful APIs, containerization (Docker), and orchestration (Kubernetes); * Strong experience with code versioning (e.g., Git); * Knowledge of model monitoring tools for production environments; * Practical experience with MLOps and tools such as MLflow, Airflow, or similar; * Ability to implement AI solutions in production environments, with emphasis on scalability and security; * Experience with LLM (Large Language Model) APIs; * Strong communication skills and ability to collaborate effectively with cross-disciplinary teams. Bonus qualifications include: * Knowledge of governance and security techniques applied to generative AI; * Experience with RAG (Retrieval\-Augmented Generation) and other advanced generative AI techniques; * Knowledge of C\# for integration with existing systems; * Experience in agile environments and methodologies such as Scrum or Kanban. We are seeking a Senior Machine Learning Engineer to work at the intersection of machine learning/deep learning, cloud technologies, and system architecture. The candidate will be responsible for designing and implementing advanced statistical models, machine learning algorithms, and generative AI solutions. The role emphasizes MLOps best practices—including code and data versioning—as well as deployment and monitoring of models in production, playing a strategic role in the development of our AI products. Your responsibilities: * Apply MLOps best practices, including data and code versioning, and model serving; * Develop end-to-end new product features; * Build robust and scalable code for production deployment; * Create pipelines for deploying and monitoring models in production; * Work on Generative Artificial Intelligence solutions; * Collaborate with cross-disciplinary teams, demonstrating strong communication and teamwork. 2512100202181673857