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# Senior ML/AI Engineer

- **Company:** CLERA, LLC
- **Location:** New York, NY, United States
- **Experience:** Expert
- **Salary:** $170,000.0 - $230,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Data Cleansing, Graph Database, Python (Programming Language), Machine Learning, Tensorflow, Software Deployment, SQL Databases, Feature Engineering, Pytorch, Large Language Models, Backend, Scikit Learn, Machine Learning Operations, Virtual Agents
- **Published:** August 5, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=bcb9ac24c704ce85

## About the Role

* 5+ years of experience in Machine Learning roles, with significant experience designing and building ML systems architecture
 * M.S. or Ph.D. in Computer Science, Machine Learning, or a related field
 * Extensive hands-on experience with Python and its ML ecosystem (e.g. PyTorch, TensorFlow, scikit-learn, LangChain)
 * Proven production experience building and deploying end-to-end ML systems
 * Experience building agentic AI harnesses for production use cases
 * Strong foundational ML knowledge beyond LLM application (classical ML, statistics, time series, etc.)
 * Experience with graph databases
 * Proficiency with SQL, * Experience working in startup environments or at large-scale tech companies

## Description

Join a fast-growing, AI-native consumer intelligence platform serving the world's largest retailers and brands. This is a rare opportunity to work at the intersection of cutting-edge AI research and real enterprise deployment - building the intelligent systems at the very core of the product. The platform reasons, forecasts, and acts autonomously across complex enterprise data landscapes, delivering demand forecasting, consumer intelligence, competitive analysis, and autonomous decision-making at scale., * Design, build, and deploy ML models for demand forecasting, time series prediction, consumer sentiment analysis, and anomaly detection at enterprise scale

 * Develop and iterate on the platform's agentic AI architecture - building systems that reason across heterogeneous data sources and take autonomous action
 * Build and maintain robust ML pipelines: data preprocessing, feature engineering, model training, evaluation, and production deployment
 * Architect RAG systems and LLM integrations that power natural language interfaces and autonomous workflows
 * Collaborate with backend engineers to ensure models are production-grade - optimized for latency, reliability, and scale
 * Own model performance end-to-end: monitoring, retraining, and continuous improvement in production
 * Stay at the frontier of AI research and bring relevant innovations into the platform


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