Senior Machine Learning Engineer
Core
Design, develop, and deploy scalable machine learning models that perform, scale, and deliver measurable business impact in production environments.
Role type
Senior Machine Learning Engineer (Production)
Builds
Production ML models, end-to-end ML pipelines, and scalable AI systems
Domain
Applied AI, Data Engineering, Cloud Infrastructure
Deliverable
production ML models
Required skills
Python, TensorFlow, PyTorch, Scikit-learn, model deployment (APIs/microservices), ML algorithms (supervised/unsupervised/deep learning/NLP), distributed systems (Spark/Hadoop), cloud platforms (AWS/GCP/Azure), data structures, algorithms, software engineering best practices
Preferred skills
MLOps tools (MLflow/Kubeflow/Airflow), GenAI/LLM applications, A/B testing frameworks, scaling ML systems in production
Technologies
TensorFlow, PyTorch, Scikit-learn, Spark, Hadoop, AWS, GCP, Azure, MLflow, Kubeflow, Airflow
Responsibilities
Design and deploy scalable ML models in production; translate business problems into structured ML solutions with clear metrics; own end-to-end ML pipelines from data ingestion to monitoring; collaborate with data engineers on reliable data pipelines; optimize models for performance, latency, and cost; evaluate and retrain models based on drift; mentor junior engineers
Seniority
Senior, hands-on IC