11 hours ago
Base Salary
$170k - $230k/yr
Responsibilities
- Design, build, and deploy ML models for demand forecasting, time series prediction, consumer sentiment analysis, and anomaly detection.
- Develop and iterate on agentic AI architectures that reason across heterogeneous data sources and take autonomous action.
- Build and maintain ML pipelines for data preprocessing, feature engineering, model training, evaluation, and production deployment.
- Architect RAG systems and LLM integrations for natural language interfaces and autonomous workflows.
- Collaborate with backend engineers to deliver models optimized for latency, reliability, and scale.
- Own production model monitoring, retraining, performance optimization, and continuous improvement.
- Track AI research and incorporate relevant innovations into the platform.
Requirements
- M.S. or Ph.D. in Computer Science, Machine Learning, or a related field.
- At least 3 years of experience building and delivering production ML pipelines and ML systems architecture.
- Deep proficiency in Python and ML frameworks such as PyTorch or TensorFlow.
- Production experience building agentic systems or LLM harnesses for real-world use cases.
- Hands-on experience with graph databases such as Neo4j or Amazon Neptune.
- Strong SQL proficiency for data querying and manipulation.
- Experience with large-scale ML teams, established technology companies, or early-stage ML-focused startups is preferred.
- Experience with Go is preferred.
- Must be based in the United States and eligible to work without visa sponsorship.
Benefits
- On-site work in New York, New York.
- No visa sponsorship is available.