30/05/2026
Job title: Senior ML/AI Engineer
📌Location: New York City
Salary: $180,000 - $225,000
Work Schedule: Hybrid
📍Work type: Full time
Number of hires : 2hires
Job Summary
As a Senior ML/AI Engineer, you'll build and deploy the intelligent systems at the core of company's platform. You'll develop the models and agentic architectures that power demand forecasting, consumer intelligence, competitive analysis, and autonomous decision-making.
Key Responsibilities
- 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 company'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 and improve the production graph RAG system — a core technical differentiator
- 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.
Requirements
- 5+ years of experience in applied machine learning and AI, with models deployed and running in production environments
- M.S. or Ph.D. in Computer Science, Machine Learning, Statistics, or related field (or equivalent practical experience — what you've built matters more than the degree)
- Deep proficiency in Python with experience in ML frameworks (PyTorch, TensorFlow, scikit-learn)
- Strong background in statistical analysis, predictive modeling, and time series forecasting
- Experience with applied agentic AI/ML systems and multi-agent orchestration
- Experience with NLP, LLMs, and RAG architectures.
Bonus Skills
- Experience with graph databases or graph RAG systems (major plus — core to Merciv's stack)
- Background in retail, supply chain, or demand forecasting domains
- Experience with graph neural networks or knowledge graphs
- Familiarity with MLOps platforms and model serving infrastructure
- Contributions to open-source ML/AI projects or published research
Ideal Background
- Senior applied ML engineer from a high-agency, innovation-driven company working at the fringes of modern AI.
- Target companies: Palantir (ontology/graph experience), Cognition, Harvey, Rogo, Cursor, and similar verticalized AI intelligence layers.
- Also strong: ML engineers from enterprise data companies (Databricks, Snowflake ecosystem), retail tech (demand forecasting, pricing), NLP-heavy product companies, or applied AI startups who have deployed models at scale.
Send CV to [email protected] or DM