AI ML Engineer

Company: Maynor Consulting

Website: Visit Website

Business Type: Small/Medium Business

Company Type: Product

Business Model: B2B2C

Funding Stage: Series A

Industry: Ecommerce

Salary Range: ₹ 15-40 Lacs PA

Job Description

This is a permanent role with Series A funded startup in e-commerce domain - A valued client of Maynor Consulting.

Role

Build real-time AI for next-gen retail automation

Tote.ai is building AI-powered systems for convenience stores and fuel stations, enabling faster self-checkout, personalized offers, persistent carts, real-time assistance, and in-store recommendations. We operate at the intersection of AI + retail + automation + high-performance backend systems.

We’re looking for an AI/ML Engineer who can take ML models from data → training → deployment → monitoring in a real-world retail environment.

What You’ll Do (Core Responsibilities)

• Build & integrate AI/ML models
• Recommendation engines, personalized offers & upsell models
• Customer behavior prediction & fraud detection
• Demand forecasting and inventory intelligence
• Checkout optimization & real-time inference models
• Work with multi-source retail data
• Clean, transform, and preprocess transaction logs, sales data, customer history, inventory data, and sensor streams
• Create robust features and training pipelines for production workloads
• Deploy ML models into production
• Convert ML models into APIs/microservices
• Integrate with POS, checkout systems, and backend infra
• Ensure low latency, high reliability, and scalability
• Maintain & monitor AI systems
• Track model performance and data drift
• Retrain, version, and optimize models
• Ensure uptime for systems tied to checkout, payments, and recommendations
• Work cross-functionally
• Collaborate with product, backend, data engineering, DevOps, and store-ops teams
• Translate retail/business needs into AI solutions
• Prototype, iterate, and deploy solutions end-to-end
• (Optional but valuable) Research & improvement
• Experiment with new ML techniques
• Optimize architectures for recommendations, forecasting, and personalization
  
  

• Strong Python skills (NumPy, Pandas, PyTorch/TensorFlow)
• Solid understanding of ML fundamentals (statistics, probability, linear algebra)
• Hands-on experience with supervised/unsupervised learning
• Track record of building & deploying ML models in production
  
  

• APIs/microservices (FastAPI/Flask)
• MLOps (Docker, CI/CD, monitoring)
• Data pipelines & large datasets
• Databases or streaming data systems
  
  

• Experience with real-time systems or low-latency inference
• Knowledge of recommendation systems or demand forecasting
• Retail/e-commerce/fintech ML experience
• Exposure to computer vision or sensor data
  
  

• 2+ years of hands-on ML/AI engineering
  
  

• B.E./B.Tech or higher in Computer Science, IT, Data Science, or related fields
• Premier college background preferred, not mandatory
  
  

• Someone who loves building real products, not just experimental notebooks
• Ownership mindset — you care about reliability in real-time scenarios
• Enjoys working at the intersection of AI + backend + product
• Strong communicator who works well across teams