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Full time 🤖 AI / ML

AI Engineer (Marketing AI / ML Engineer) at Morningstar

Listed by DevShelfHub

Vashi, Navi Mumbai, India (4 days office)
Hybrid
Mid-level · 1–3 yrs

About the Role

Morningstar is hiring an AI Engineer for the Analytics Engineering team within Marketing Intelligence and Operations (MIOps) in Vashi, Navi Mumbai to build AI-driven systems for marketing measurement, automation, and insight generation.

The role works across ML, generative AI, and agent-based automation with 4 days working from office.

Position Overview

Build and operationalize AI-driven systems improving marketing measurement, automating workflows, and scaling insight generation. Partner with Marketing, Analytics, and Engineering to embed AI into how marketing work gets done — combining ML, GenAI, and analytics engineering.

What you'll do

  • Design, develop, and deploy ML and generative AI solutions for marketing
  • Build scalable data and model pipelines (prep, modeling, evaluation, deployment, monitoring)
  • Develop GenAI capabilities: prompt workflows, embeddings, and RAG
  • Contribute to AI agents and automation workflows for marketing analysis
  • Partner with Marketing and Analytics to translate business needs into solutions
  • Perform data preparation, feature engineering, and validation
  • Integrate AI outputs into dashboards, tools, and downstream workflows
  • Document systems, models, and outputs for transparency

What we're looking for

  • Bachelor's degree required; Master's preferred
  • 1–3 years experience in AI, ML, or data science
  • Strong quantitative and programming foundation

Eligibility Criteria

  • Bachelor's degree required; Master's preferred
  • 1–3 years experience in AI, ML, or data science
  • Strong quantitative and programming foundation

Skills & Technologies

Required

Bachelor's degree; Master's preferred in quantitative field 1–3 years AI, ML, or data science experience Machine learning and generative AI solution development GenAI: prompt workflows, embeddings, RAG patterns Scalable data and model pipelines across ML lifecycle Python and modern ML/AI frameworks Data preparation, feature engineering, and validation Documentation for transparency and usability

Benefits & Perks

  • Health Insurance
  • Flexible Leave Policy
  • Learning Budget
  • EPF / NPS

Why This Role is Good for Experienced Professionals

  • Full ML lifecycle exposure in marketing AI context
  • GenAI and RAG workflow development experience
  • Agent-based automation for real business problems
  • Cross-functional collaboration with Marketing and Analytics
  • Modern marketing intelligence ecosystem
  • Hybrid work with structured office collaboration
  • Early-career role with production system impact
  • Interpretable, reliable AI aligned to business context

Frequently Asked Questions

What experience is required?

1–3 years in AI, ML, or data science roles.

What is the work location?

Vashi, Navi Mumbai with 4 days working from office.

What AI technologies are used?

Machine learning, generative AI, RAG, embeddings, and agent-based automation.

What team will I join?

Analytics Engineering within Marketing Intelligence and Operations (MIOps).

What education is required?

Bachelor's required; Master's preferred in a quantitative field.

Is this a single-model role?

No — the role embeds AI across marketing measurement, experimentation, and operations.

Why Join Morningstar?

  • Build production AI for marketing intelligence
  • Work across ML, GenAI, and analytics engineering
  • Partner with Marketing and Analytics teams
  • Hybrid model with Navi Mumbai office
  • Help marketing move faster with embedded AI
  • Document-driven transparent AI systems

About Morningstar

Morningstar provides independent investment research and data-driven insights. The MIOps team builds marketing intelligence combining ML, GenAI, and analytics engineering.
Industry
Technology
Company Size
500+
Website
morningstar.com
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Job Details

Type
Full time
Level
Mid-level
Experience
1–3 years
Location
Vashi, Navi Mumbai, India (4 days office)
Work Mode
Hybrid
Category
AI / ML

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