Description

Key Responsibilities
End-to-End AI/ML Development: Design, build, train, validate, and deploy production-ready machine learning models into live operational environments. Continuously monitor model performance, ensuring high accuracy and reliability.
Design and deploy: AI agents that automate complex, multi-step operational decision-making and workflows.
Operational Automation & Optimization: Automate repetitive operational workflows, reporting processes, and decision-making systems to deliver measurable efficiency gains.
Data Engineering & Pipeline Construction: Build robust ETL/data pipelines to ingest, clean, and process structured and unstructured operational datasets (e.g., inventory, routing, labor, service events).
Systems Integration: Seamlessly connect AI tools and predictive models into existing warehouse, logistics, and operational software systems. Rapidly prototype tools for immediate business impact.
Cross-Functional Collaboration: Partner with non-technical and technical teams (Operations, Finance, Facilities, Procurement, IT) to identify inefficiencies, gather requirements, and deploy decision-support dashboards.
AI Governance & Safety: Ensure the responsible deployment of AI systems. This includes rigorous model validation, documentation of assumptions, mitigating risk and bias, ensuring data governance and security, and building fail-safes into automated operational decisions.
Target Operational AI Use Cases
We are specifically looking for candidates who can build and deploy solutions for:
Logistics & Routing: Route and delivery optimization, predictive maintenance for vehicles/equipment.
Workforce & Labor: Labor scheduling optimization, capacity planning, and workload balancing across warehouses.
Supply Chain & Inventory: Inventory discrepancy detection, automated inventory reconciliation, demand forecasting, and predicting supply needs.
Facilities & Operations: Managing facility expenses (housekeeping, maintenance), anomaly detection in operational data, cost optimization modeling, and utilizing computer vision for document, barcode, or label recognition.

Required Technical Capabilities & Tech Stack Core Programming & Databases Python (Required): Must be the primary development language, with demonstrated hands-on ability to build and deploy AI-driven operational solutions.
SQL (Required): Advanced ability to query and manage relational databases (PostgreSQL, SQL Server, or MySQL).
Enterprise AI Agent Platforms & Orchestration: Proven experience building, deploying, and scaling agentic workflows and Retrieval-Augmented Generation (RAG) solutions using platforms such as Gemini Enterprise, n8n, and LangChain Required Python Libraries & Frameworks Data Processing: Pandas, NumPy Machine Learning: Scikit-learn, XGBoost Data Visualization: Matplotlib, Plotly, Seaborn Automation / Integration: FastAPI, Flask Deep Learning (Preferred): TensorFlow or PyTorch Computer Vision (Preferred): OpenCV Optimization (Preferred): OR-Tools Data Engineering & Integration Proficiency in handling APIs, REST services, and JSON/CSV data.
Strong ability to handle large-scale operational data and ensure data reliability/quality.
Version Control: Git (Required).
Cloud Platforms (Preferred): AWS, Azure, or Google Cloud.
Event Streaming (Preferred): Message queues or event streaming architecture.
Candidate Qualifications & Profile
Education: Bachelor’s degree in a quantitative field (Computer Science, Data Science, Engineering, Mathematics, or similar).
Experience: 5+ years of hands-on, applied experience in AI/ML engineering, data science, or advanced analytics.
Industry Background: Preference for candidates with a background in logistics, transportation, supply chain, warehousing, or field operations.
Core Competencies: * Strategic Problem Solver: Ability to look at operational friction points and design AI solutions to fix them.
Communicator: Capable of explaining complex model outputs and AI strategies to business leaders.
Builder: A hands-on creator who values rapid prototyping and measurable business impact over theoretical research

Key Skills

Education

Bachelor's degree