We are seeking a versatile and passionate AI / Machine Learning Engineer to join our data science and engineering team. You will be instrumental in bridging the gap between data science research and production-ready applications, building scalable machine learning systems that drive business value. This role requires a strong balance of software engineering principles and ML expertise.
Key Responsibilities
- Design, develop, and implement end-to-end Machine Learning pipelines for training, testing, and deployment of predictive models.
- Work closely with Data Scientists to translate prototypes and models into scalable, production-grade code (MLOps).
- Develop robust, efficient, and well-documented code primarily using Python and relevant ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
- Implement monitoring and alerting solutions for models in production to track performance, detect drift, and ensure reliability.
- Collaborate with Data Engineers to ensure efficient data preparation, feature engineering, and access to necessary data infrastructure.
- Stay current with the latest advancements in AI, ML techniques, and scalable infrastructure.
- 3+ years of professional experience in a Machine Learning Engineer, AI Developer, or similar role.
- Strong expertise in Python and object-oriented programming, with a focus on code quality and best practices.
- Mandatory practical experience with major Machine Learning frameworks (e.g., TensorFlow, PyTorch) and libraries (e.g., scikit-learn).
- Solid understanding of MLOps principles and the tools required for model deployment, versioning, and lifecycle management (e.g., MLflow, Kubeflow, or similar).
- Proficiency in SQL and experience working with large datasets and data warehousing concepts.
- Excellent analytical and problem-solving skills, with the ability to communicate complex technical concepts effectively.
- Experience working with Cloud platforms (AWS, GCP, or Azure) for model deployment, compute, and storage (e.g., SageMaker, Vertex AI, Azure ML Services).
- Knowledge of containerization technologies (Docker, Kubernetes) for building reproducible and scalable ML environments.
- Familiarity with distributed computing frameworks (e.g., Spark).
- Advanced degree (M.S. or Ph.D.) in Computer Science, Engineering, or a related quantitative field.
- Very good level of English, both spoken and written, for effective communication with international teams;
The Devoteam Group works for equal opportunities, promoting its employees based on merit and actively fights against all forms of discrimination. We are convinced that diversity contributes to the creativity, dynamism and excellence of our organization. All of our vacancies are open to people with disabilities.
