Machine Learning Engineer with an Agentic Focus

About the role

We are looking for a Machine Leaning Engineer (MLE) to design, build, and optimize our machine learning operation. You will play a crucial role in scaling AI models from research to production, ensuring smooth model deployment, monitoring, and lifecycle management across our Google Cloud Platform (GCP) infrastructure.

What you'll do

• Design, develop, and deploy machine learning models and solutions, leveraging tools such as LangGraph and MLflow for orchestration and lifecycle management
• Collaborate on building and maintaining scalable data and feature pipeline infrastructure for real time and batch processing using tools like BigQuery, BigTable
• Develop and implement robust strategies for model monitoring and observability to detect model drift, bias, and performance degradation
• Optimize ML model inference performance to improve latency and cost-efficiency of AI applications
• Ensure the overall reliability, performance, and scalability of the ML models and data infrastructure platform

What you need

• 1–4 yrs of experience
• Machine learning
• Python
• Scikit-learn
• ETL
• BigQuery
• Airflow
• Any graduate

Good to have

• TensorFlow
• PyTorch
• GCP
• Kubernetes
• Docker
• MLOps