Senior Machine Learning Engineer
We are looking for a Senior Machine Learning Engineer to join our team and drive the development, deployment, and support of advanced ML solutions in a production environment. You will work in a cross-functional team, implement engineering best practices, automate ML processes, and integrate models into complex data-driven systems.
Responsibilities
- Design, develop, and maintain production-grade machine learning models
- Automate ML pipelines using modern tools (e.g., Databricks, Azure ML, AWS SageMaker)
- Integrate ML solutions into complex data-driven systems
- Work with large-scale data using Apache Spark or alternative technologies
- Apply and promote engineering best practices and MLOps principles
- Collaborate with Data Science, Data Engineering, DevOps, and other teams
- Support various data processing paradigms (batch, micro-batch, streaming)
- Utilize cloud platforms (AWS, GCP, Azure) for deploying and maintaining ML solutions
Requirements
- 3+ years of experience as a Machine Learning Engineer in production projects
- Practical experience with cloud platforms (AWS, GCP, Azure)
- Experience with MLOps platforms/technologies (AWS SageMaker, Azure ML, Databricks, GCP Vertex AI)
- Hands-on experience with the Python ML ecosystem (NumPy, pandas, XGBoost, Keras, PyTorch, TensorFlow, scikit-learn)
- Experience with creating microservices for model serving
- Experience with Apache Spark (Spark SQL, MLlib/Spark ML) or alternative technologies
- Experience automating pipelines and workflow management (Airflow, Argo Workflow, etc.)
- Proficiency in modern engineering practices (CI/CD, git, GitHub, Docker)
- Experience with different data processing paradigms (batch, micro-batch, streaming)
- Excellent communication skills and experience working in cross-functional teams
- English language proficiency at an Upper-Intermediate level (B2) or higher
