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, Google Cloud Platform, 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, Google Cloud Platform, Azure) Experience with MLOps platforms/technologies (AWS SageMaker, Azure ML, Databricks, Google Cloud Platform 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
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- Dice Id: 10330481
- Position Id: fdaf3b3bd3c1698a22db16cd5a450b39
- Posted 30+ days ago