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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