Sr. Machine Learning Engineer
Core
Design, develop, and deploy scalable machine learning solutions and AI features in production environments to drive strategic decision-making.
Role type
Senior Machine Learning Engineer (MLOps & Production)
Builds
End-to-end ML pipelines, scalable ML systems, and production-grade AI features
Domain
Cloud infrastructure, MLOps, and large-scale data platforms
Deliverable
production ML models
Required skills
PyTorch, TensorFlow, Python, Kubernetes, Docker, Cloud Composer/Airflow, SQL, Snowflake/DataBricks/BigQuery, MLOps practices
Preferred skills
LangChain, LangGraph, RAG/LLM-based systems, distributed systems, streaming data pipelines, Cloud Architecture certifications
Technologies
PyTorch, TensorFlow, Docker, Kubernetes, Cloud Composer, Airflow, AWS, Azure, GCP, Snowflake, DataBricks, BigQuery
Responsibilities
Architect and deploy end-to-end ML pipelines for production workloads; Design scalable and resilient ML systems; Operationalize ML models using containerized environments and orchestration tools; Integrate ML solutions with data warehouses; Ensure CI/CD best practices for ML deployments; Optimize model performance and system efficiency
Seniority
Senior, hands-on IC