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 environments
- Knowledge of cloud platforms (AWS, GCP, Azure) in professional applications
- Background in MLOps technologies such as AWS SageMaker, Azure ML, Databricks, or GCP Vertex AI
- Skills in Python ML tools like NumPy, pandas, XGBoost, Keras, PyTorch, TensorFlow, and scikit-learn
- Expertise in microservices design for model deployment
- Familiarity with Apache Spark (e.g., Spark SQL, Spark MLlib) or similar technologies
- Proficiency in automating workflows with tools like Airflow or Argo Workflow
- Competency in CI/CD practices, version control (e.g., git, GitHub), and containerization with Docker
- Understanding of diverse data processing approaches (batch, micro-batch, streaming)
- Strong interpersonal and cross-functional team collaboration skills
- English proficiency at Upper-Intermediate (B2) level or above
