About the RoleThis 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 & BenefitsSalary: $170,000 - $230,000 USD annually. Visa sponsorship is not available.
LocationOn-site in
New York, NY.
