About the Role
This is a senior individual contributor role on the core AI team of an early-stage, AI-native consumer intelligence platform serving large enterprise retail clients. You'll own the intelligent systems that power demand forecasting, consumer sentiment analysis, competitive benchmarking, and autonomous decision-making - applied AI with direct, measurable business impact.
What You'll Do
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 an agentic AI architecture that reasons across heterogeneous data sources and takes autonomous action.
Build and maintain robust ML pipelines covering data preprocessing, feature engineering, model training, evaluation, and production deployment.
Architect RAG systems and LLM integrations powering 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 current with AI research and bring relevant innovations into the platform.
What We're Looking For
M.S. or Ph.D. in Computer Science, Machine Learning, or a related field.
3+ years of ML-focused experience building and delivering production ML pipelines and systems architecture - not purely general software engineering.
Deep proficiency in Python and ML frameworks such as PyTorch, TensorFlow, or equivalent.
Production experience building agentic systems or LLM harnesses for real-world use cases.
Hands-on experience with graph databases (e.g. Neo4j, Amazon Neptune, or equivalent).
Strong SQL proficiency for data querying and manipulation.
Background at scale - large tech organizations, established ML teams, or early-stage ML-focused startups.
Experience with the Go programming language is a plus.
Compensation & Benefits
Salary: $170,000 - $230,000 USD annually. Visa sponsorship is not available.
Location
On-site in New York, NY.

