Lead Data & ML Engineer

7-Eleven Global Solution Center – India; Bengaluru; On-site; INR 1,800,000 - 2,400,000; Full time

Job summary

7-Eleven Global Solution Center – India is seeking a senior ML lead to design, develop, and productionize AI-powered products. You will own ML initiatives from concept through deployment, building scalable, maintainable services and collaborating with stakeholders.

The role requires 3-5 years of ML experience and deep hands-on expertise with TensorFlow, PyTorch, and Generative AI, plus experience deploying via Docker and Kubernetes in an Azure data environment.

Qualifications

• 3-5 years of experience in Machine Learning and data modeling.
• ],
• job_responsibilities_description
• CoT_job_summary_short achar
• JOB_SUMMARY_PLACEHOLDER
• perks
• stated_min
• stated_max
• stated_absolute
• salary_estimation_cot
• estimated_low
• estimated_medium
• estimated_high
• currency
• frequency
• bonus
• tax
• application_email
• job_end_date
• contact_person
• hiring_department_name
• CoT_job_summary_short
• COMPANY NAME: 7-Eleven Global Solution Center – IndiaKEY POINTS: ML leadership, productionization, Azure data stack, distributed teams
• job_summary_short
• <p>7-Eleven Global Solution Center – India is seeking a senior ML lead to design, develop, and productionize AI-powered products. You will own ML initiatives from concept through deployment, building scalable, maintainable services and collaborating with stakeholders.</p><p>The role requires 3-5 years of ML experience and deep hands-on expertise with TensorFlow, PyTorch, and Generative AI, plus experience deploying via Docker and Kubernetes in an Azure data environment. You will mentor a distributed team in an Agile, DevOps setup.</p>
• contract_type
• fulltime
• location_type
• on site
• remote_scope
• null
• perks
• []
• stated_min
• null
• stated_max
• null
• stated_absolute
• null
• salary_estimation_cot
• 7-Eleven Global Solution Center – India: expected salary in the Indian market for senior ML lead in Bengaluru; INR range around 18-24 LPA based on experience and Azure data stack.
• estimated_low
• $default
• estimated_medium
• $default
• estimated_high
• $default
• currency
• frequency
• bonus
• tax
• application_email
• job_end_date
• contact_person
• hiring_department_name

Responsibilities

• Lead design, development, and productionization of ML and AI-driven products.
• Own ML initiatives from conceptualization through deployment and continuous improvement.
• Develop scalable, reusable, and maintainable ML service components with quality-first principles.
• Build and deploy ML, Deep Learning, Generative AI, and Agentic AI solutions.
• Design and expose ML services using FastAPI and RESTful APIs.
• Collaborate with business stakeholders to translate requirements into technical solutions.
• Ensure robustness, scalability, performance, and maintainability of ML applications.
• Lead and mentor team members, fostering technical growth and best practices.
• Work in an Agile, DevOps-driven environment with distributed teams.
• Quickly learn and adopt new technologies as required to deliver results.

Skills

ML & data modeling

Deep Learning

LLMs

TensorFlow

PyTorch

Generative AI

Agentic AI

SQL

Data analysis

Spark (PySpark)

Azure Data Services

Python

FastAPI

REST APIs

Docker

Kubernetes

Databricks

Power BI

MySQL

MongoDB

Kafka

Education

Bachelor’s degree in computer science

Tools

TensorFlow

PyTorch

Glean

Agent Bricks

FastAPI

RESTful services

Docker

Kubernetes

Databricks

Synapse Notebooks

Azure Data Services

MySQL

PostgreSQL

MongoDB

Kafka

Kinesis

RabbitMQ

Job description

• Lead the design, development, and productionization of machine learning and AI-driven products
• Own ML initiatives from conceptualization through deployment and continuous improvement
• Develop scalable, reusable, and maintainable ML service components with quality-first principles
• Build and deploy ML, Deep Learning, Generative AI, and Agentic AI solutions
• Design and expose ML services using FastAPI and RESTful APIs
• Collaborate with business stakeholders to translate requirements into technical solutions
• Ensure robustness, scalability, performance, and maintainability of ML applications
• Lead and mentor team members, fostering technical growth and best practices
• Work in an Agile, DevOps-driven environment with distributed teams
• Quickly learn and adopt new technologies as required to deliver results

Skills

Key Skills Required:

• 3-5 years of experience in Machine Learning and data modeling
• Strong experience in Machine Learning, Deep Learning, and Large Language Models (LLMs)
• Hands‑on expertise with TensorFlow, PyTorch, and ML libraries
• Proficiency in Generative AI and Agentic AI, including automation use cases
• Experience with agentic AI platforms such as Glean and Agent Bricks
• Experience in developing and productionizing ML applications
• 7+ years of experience in statistics and analytics on large-scale datasets
• Strong SQL and data analysis skills, including SQL DW concepts
• Experience with Spark ecosystem: PySpark, Databricks, Synapse Notebooks (1+ year hands‑on)
• Proficiency in Azure Data Services:
• Azure security model
• Experience building pipelines for full and incremental data loads from Azure and on‑prem sources
• Strong knowledge of data management, processing, cleaning, transformation, aggregation, and modeling
• Working knowledge of Power BI reports and dashboards (AAS / PBI)
• Strong programming skills in Python (Java is a plus)
• Experience with FastAPI, RESTful services, and microservices architecture
• Proficiency with databases such as MySQL, PostgreSQL, and MongoDB
• Experience deploying applications using Docker and Kubernetes
• Experience with streaming and messaging systems: Kafka, Kinesis, RabbitMQ
• Familiarity with Azure Git and DevOps practices

Leadership & Soft Skills

• Strong mentoring and team leadership experience
• Excellent written and verbal communication skills
• Ability to work effectively in distributed teams
• Strong understanding of data structures and design patterns
• Exposure to the retail industry is a plus

Education:

• Bachelor’s degree in computer science or a related field (required)