Solutions Architect - Machine Learning
Core
Design, develop, deploy, and optimize production-grade machine learning models and end-to-end ML solutions, ensuring scalability, security, and maintainability.
Role type
Senior IC Solutions Architect (Machine Learning)
Builds
Production ML models, data pipelines, and scalable inference services
Domain
Machine Learning Engineering and MLOps
Deliverable
production ML models
Required skills
Python, PyTorch, TensorFlow, scikit-learn, XGBoost, Apache Spark, Kubernetes, MLOps, CI/CD/CT, Model Monitoring
Preferred skills
Scala, Java, ONNX, Hugging Face Transformers, Azure/AWS/GCP, Terraform
Technologies
Python, PyTorch, TensorFlow, scikit-learn, XGBoost, LightGBM, CatBoost, NumPy, pandas, Polars, Hugging Face, ONNX, Apache Spark, Databricks, Airflow, Kafka, Snowflake, MLflow, Azure ML, SageMaker, Vertex AI, Feast, Kubeflow, FastAPI, BentoML, KServe, Docker, Kubernetes, Terraform, Prometheus, Grafana
Responsibilities
Lead end-to-end architecture of ML solutions from data ingestion to model serving; Design and optimize ML models and adopt new algorithms; Build and oversee batch and streaming data pipelines; Define model evaluation strategies and metrics; Lead model packaging, deployment, and CI/CD/CT pipelines; Own production health, monitoring, and incident triage for ML systems; Establish ML engineering best practices and mentor team members.
Seniority
Senior, hands-on IC with leadership responsibilities
