AI/ML Engineer

at Vijay Sales

AI/ML Engineer

Vijay Sales

Company

Home

AI/ML Engineer

at Vijay Sales

Posted by Tech Recruiter

1 - 6 yrs

₹6L - ₹15L / yr

Pune

Skills

databricks

SQL

Python

Artificial Intelligence (AI)

Generative AI

Data Visualization

About Vijay Sales

Vijay Sales is one of India’s leading electronics retail brands with 160+ stores nationwide and a fast-growing digital presence. We are on a mission to build the most advanced data-driven retail intelligence ecosystem—using AI, predictive analytics, LLMs, and real-time automation to transform customer experience, supply chain, and omnichannel operations.

Role Overview

We are looking for a highly capable AI Engineer who is passionate about building production-grade AI systems, designing scalable ML architecture, and working with cutting-edge AI/ML tools. This role involves hands-on work with Databricks, SQL, PySpark, modern LLM/GenAI frameworks, and full lifecycle ML system design.

Key Responsibilities

Machine Learning & AI Development

Build, train, and optimize ML models for forecasting, recommendation, personalization, churn prediction, inventory optimization, anomaly detection, and pricing intelligence.
Develop GenAI solutions using modern LLM frameworks (e.g., LangChain, LlamaIndex, HuggingFace Transformers).
Explore and implement RAG (Retrieval Augmented Generation) pipelines for product search, customer assistance, and support automation.
Fine-tune LLMs on company-specific product and sales datasets (using QLoRA, PEFT, and Transformers).
Develop scalable feature engineering pipelines leveraging Delta Lake and Databricks Feature Store.

Databricks / Data Engineering

Build end-to-end ML workflows on Databricks using PySpark, MLflow, Unity Catalog, Delta Live Tables.
Optimize Databricks clusters for cost, speed, and stability.
Maintain reusable notebooks and parameterized pipelines for model ingestion, validation, and deployment.
Use MLflow for tracking experiments, model registry, and lifecycle management.

Data Handling & SQL

Write advanced SQL for multi-source data exploration, aggregation, and anomaly detection.
Work on large, complex datasets from ERP, POS, CRM, Website, and Supply Chain systems.
Automate ingestion of streaming and batch data into Databricks pipelines.

Deployment & MLOps

Deploy ML models using REST APIs, Databricks Model Serving, Docker, or cloud-native endpoints.
Build CI/CD pipelines for ML using GitHub Actions, Azure DevOps, or Databricks Workflows.
Implement model monitoring for drift, accuracy decay, and real-time alerts.
Maintain GPU/CPU environments for training workflows.

Must-Have Technical Skills

Core AI/ML

Strong fundamentals in machine learning: regression, classification, time-series forecasting, clustering.
Experience in deep learning using PyTorch or TensorFlow/Keras.
Expertise in LLMs, embeddings, vector databases, and GenAI architecture.
Hands-on experience with HuggingFace, embedding models, and RAG.

Databricks & Big Data

Hands-on experience with Databricks (PySpark, SQL, Delta Lake, MLflow, Feature Store).
Strong understanding of Spark execution, partitioning, and optimization.

Programming

Strong proficiency in Python.
Experience writing high-performance SQL with window functions, CTEs, and analytical queries.
Knowledge of Git, CI/CD, REST APIs, and Docker.

MLOps & Production Engineering

Experience deploying models to production and monitoring them.
Familiarity with tools like MLflow, Weights & Biases, or SageMaker equivalents.
Experience in building automated training pipelines and handling model drift/feedback loops.

Preferred Domain Experience

Retail/e-commerce analytics
Demand forecasting
Inventory optimization
Customer segmentation & personalization
Price elasticity and competitive pricing

About Vijay Sales

Role Overview

Key Responsibilities

Machine Learning & AI Development

Build, train, and optimize ML models for forecasting, recommendation, personalization, churn prediction, inventory optimization, anomaly detection, and pricing intelligence.
Develop GenAI solutions using modern LLM frameworks (e.g., LangChain, LlamaIndex, HuggingFace Transformers).
Explore and implement RAG (Retrieval Augmented Generation) pipelines for product search, customer assistance, and support automation.
Fine-tune LLMs on company-specific product and sales datasets (using QLoRA, PEFT, and Transformers).
Develop scalable feature engineering pipelines leveraging Delta Lake and Databricks Feature Store.

Databricks / Data Engineering

Build end-to-end ML workflows on Databricks using PySpark, MLflow, Unity Catalog, Delta Live Tables.
Optimize Databricks clusters for cost, speed, and stability.
Maintain reusable notebooks and parameterized pipelines for model ingestion, validation, and deployment.
Use MLflow for tracking experiments, model registry, and lifecycle management.

Data Handling & SQL

Write advanced SQL for multi-source data exploration, aggregation, and anomaly detection.
Work on large, complex datasets from ERP, POS, CRM, Website, and Supply Chain systems.
Automate ingestion of streaming and batch data into Databricks pipelines.

Deployment & MLOps

Deploy ML models using REST APIs, Databricks Model Serving, Docker, or cloud-native endpoints.
Build CI/CD pipelines for ML using GitHub Actions, Azure DevOps, or Databricks Workflows.
Implement model monitoring for drift, accuracy decay, and real-time alerts.
Maintain GPU/CPU environments for training workflows.

Must-Have Technical Skills

Core AI/ML

Strong fundamentals in machine learning: regression, classification, time-series forecasting, clustering.
Experience in deep learning using PyTorch or TensorFlow/Keras.
Expertise in LLMs, embeddings, vector databases, and GenAI architecture.
Hands-on experience with HuggingFace, embedding models, and RAG.

Databricks & Big Data

Hands-on experience with Databricks (PySpark, SQL, Delta Lake, MLflow, Feature Store).
Strong understanding of Spark execution, partitioning, and optimization.

Programming

Strong proficiency in Python.
Experience writing high-performance SQL with window functions, CTEs, and analytical queries.
Knowledge of Git, CI/CD, REST APIs, and Docker.

MLOps & Production Engineering

Experience deploying models to production and monitoring them.
Familiarity with tools like MLflow, Weights & Biases, or SageMaker equivalents.
Experience in building automated training pipelines and handling model drift/feedback loops.

Preferred Domain Experience

Retail/e-commerce analytics
Demand forecasting
Inventory optimization
Customer segmentation & personalization
Price elasticity and competitive pricing

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About Vijay Sales

Founded :

1967

Type :

Products & Services

Size :

5000+

Stage :

Profitable

About

Offering guests the best in quality and service has been the primary principle at Vijay Sales since its inception as a partnership firm by Mr. Nanu Gupta, a visionary with astute business acumen and foresight.A marvellous journey that began with a small Electronics Showroom at Mahim in 1967, Vijay Sales has since evolved and has become one of India’s biggest retail chains.

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