Engineering Manager- AI & ML (Navi Mumbai)

As an Engineering Manager, AI & ML (Data Collection), you will play a critical role in building

and scaling the company's Unified AI/ML Data Collection Platform, enabling

standardized, reliable, and scalable machine learning capabilities across the organization.

This role will focus on transforming existing AI/ML and LLM-driven data systems into a

cohesive platform that supports data pipelines, model lifecycle management, evaluation

frameworks, and production deployment.

This position requires deep technical expertise in machine learning systems, ML platform

architecture, and MLOps, along with a strong ability to lead and mentor engineering teams.

You will work closely with individual contributors and cross-functional partners to ensure

that ML platform capabilities align with broader business objectives and AI/ML strategies.

You will be deeply involved in the design, development, and operationalization of platform

components, including data ingestion, feature management, model training and

evaluation, and scalable inference systems. You will provide strong technical leadership,

solve complex system-level challenges, and ensure delivery of high-quality, reliable, and

scalable ML solutions.

Your leadership will ensure that AI/ML systems are production-ready, observable, and

maintainable, with a strong emphasis on performance, cost-efficiency, and governance.

You will leverage your expertise in areas such as large language models (LLMs), retrieval

augmented generation (RAG), ML Operations (MLOps), distributed systems, and cloud

native architectures.

You will oversee the end-to-end lifecycle of ML systems—from development and

experimentation to deployment and monitoring—while ensuring alignment with global

engineering standards and business priorities.

You will be responsible for mentoring engineers, driving technical excellence, and fostering

a culture of collaboration and innovation. Your ability to partner across teams, influence

technical direction, and build high-performing teams will be critical to success in this role.

You will lead a multidisciplinary team of ML engineers responsible for building and

maintaining the Unified AI/ML Data Collection Platform. The team focuses on developing

scalable systems that support data pipelines, model lifecycle management, LLM-based

workflows, and evaluation frameworks, enabling downstream teams to build and deploy AI

driven data collection solutions.

Primary Job Responsibilities:

• AI-Powered Data Collection Systems: Lead the design and development of

scalable AI-driven data collection and enrichment workflows across structured and

unstructured data sources.

• LLM & Generative AI Workflows: Drive the implementation of LLM-based

capabilities including extraction pipelines, RAG systems, prompt orchestration,

summarization, classification, and automated validation workflows.

• Data Pipeline Engineering: Oversee high-scale ingestion, transformation, and

orchestration systems that support real-time and batch data collection processes.

• Data Quality & Evaluation: Establish frameworks for evaluating extraction quality,

model performance, hallucination risks, consistency, and overall data reliability.

• Technical Leadership: Provide hands-on leadership in architecture, system design,

operational scalability, and engineering best practices for AI-enabled data systems.

• Team Leadership & Mentorship: Build and grow a high-performing engineering

team while fostering a culture of ownership, collaboration, and continuous

improvement.

• Cross-functional Collaboration: Partner closely with product management, data

engineering, research, and business stakeholders to align technical investments

with organizational goals.

• Platform Reliability & Governance: Ensure systems meet standards for scalability,

observability, security, compliance, and auditability.

• Innovation & Continuous Improvement: Evaluate emerging AI/ML technologies,

frameworks, and tooling to improve automation capabilities and developer

productivity.

• Operational Excellence: Drive engineering best practices, Agile delivery processes,

and operational maturity across the team.

• Hiring & Talent Development: Support recruiting, onboarding, and retention efforts

while cultivating an inclusive and high-performing team environment.

• Company Leadership: Model company values and contribute to a culture of

innovation, accountability, and collaboration.

Skills and Qualifications:

• Bachelor's, Master's, or PhD in Computer Science, Engineering, Data Science, or

related field.

• 8+ years of experience in software engineering, with a focus on machine learning

systems, ML platforms, or distributed systems.

• 3+ years of experience managing engineering teams and leading technical

initiatives.

• Strong experience building production-grade ML systems, including model

deployment and lifecycle management.

• Hands-on experience with MLOps tools and practices, including CI/CD, model

monitoring, and experiment tracking (e.g., MLflow, W&B).

• Experience with pipeline orchestration and data platforms (e.g., Airflow, Dagster,

Kafka, Snowflake).

• Strong programming skills in Python and SQL, or similar languages.

• Experience with cloud platforms and containerization (e.g., AWS/GCP/Azure,

Docker, Kubernetes).

• Experience with LLM-based systems in production, including RAG pipelines,

embeddings, and vector databases.

• Solid understanding of distributed systems, scalability, and system design trade

offs.

• Proven ability to solve complex technical challenges and deliver scalable solutions.

• Excellent communication and collaboration skills, with experience working across

global teams.

• Experience working in fast-paced, data-driven environments.

Working Conditions

The job conditions for this position are in a standard office setting. Employees in this

position use PC and phones on an ongoing basis throughout the day. Limited corporate

travel may be required to remote offices or other business meetings and events.

Morningstar is an equal opportunity employer!