Manager - Automation -

GMR Group; Hyderabad; On-site; INR 3,500,000 - 7,000,000; Full time

Job summary

GMR Group seeks a senior ML/AI engineer to build, deploy and scale machine learning and GenAI across its airports, energy, infrastructure and enterprise functions.

You will lead end-to-end ML initiatives, including NLP classifiers, GenAI-enhanced predictors, and robust inference architectures in a fast-paced, product-driven environment. Strong cloud/DevOps experience and collaboration with cross-functional teams are essential.

Qualifications

• Hands-on experience in ML/AI engineering deploying models at scale.
• Proficient in Python, SQL and ML frameworks.
• Experience with cloud ML tools and DevOps practices.

Responsibilities

• Build and deploy ML/AI solutions across GMR’s verticals.
• Lead development of models, NLP classifiers, and GenAI-enabled predictors.
• Design LLM features and inference architecture.
• Own full ML lifecycle from data ingestion to deployment and drift management.

Skills

Python

SQL

scikit-learn

TensorFlow

XGBoost

PyTorch

NLP

Computer Vision

Hugging Face Transformers

Docker

Git

SageMaker / Azure ML / Google AI

Education

Engineering degree

Masters preferable

Tools

SageMaker

Azure ML Studio

Google AI

Step Functions

Lambda

Docker

Kubernetes

Job description

Role would be responsible to build, deploy, and scale machine learning and AI solutions across GMR’s verticals. This role will build and manage advanced analytics initiatives, predictive engines, and GenAI applications — with a focus on business outcomes, model performance, and intelligent automation. Reporting to the Head of Automation & AI, you will operate in a high-velocity, product-oriented environment with direct visibility of impact across airports, energy, infrastructure and enterprise functions.

ORGANISATION CHART

Head- Automation & AI --> Manager-AI & ML --> Reports To --> Position Title

KEY ACCOUNTABILITIES

AI & ML Development

• Build and deploy models using supervised, unsupervised, and reinforcement learning techniques for use cases such as forecasting, predictive scenarios, dynamic pricing & recommendation engines, and anomaly detection, with exposure to broad enterprise functions and business
• Lead development of models, NLP classifiers, and GenAI-enhanced prediction engines.
• Design and integrate LLM-based features such as prompt pipelines, fine-tuned models, and inference architecture using Gemini, Azure OpenAI, LLama etc.
• Program Plan Vs Actuals

End-to-End Solutioning

• Translate business problems into robust data science pipelines with emphasis on accuracy, explainability, and scalability.
• ⢠Own the full ML lifecycle â from data ingestion and feature engineering to model training, evaluation, deployment, retraining, and drift management.
• Program Plan Vs Actuals

Cloud , ML & data Engineering

• Deploy production-grade models using AWS, GCP, or Azure AI platforms and orchestrate workflows using tools like Step Functions, SageMaker, Lambda, and API Gateway.
• Build and optimise ETL/ELT pipelines, ensuring smooth integration with BI tools (Power BI, QlikSense or similar) and business systems.
• ⢠Data compression and familiarity with cloud finops will be an advantage, have used some tools like kafka, apache airflow or similar
• 100% compliance to processes

KEY ACCOUNTABILITIES - Additional Details

EXTERNAL INTERACTIONS

• Consulting and Management Services provider
• IT Service Providers / Analyst Firms
• Vendors

INTERNAL INTERACTIONS

• GCFO and Finance Council, Procurement council, IT council, HR Council (GHROC)
• GCMO/ BCMO

EDUCATION QUALIFICATIONS

• Engineering degree
• Masters preferable

Relevant Experience

• 5 - 8years of hands‑on experience in machine learning, AI engineering, or data science, including deploying models at scale.
• Strong programming and modelling skills in some like Python, SQL, and ML frameworks like scikit-learn, TensorFlow, XGBoost, PyTorch.
• Demonstrated ability to build models using supervised, unsupervised, and reinforcement learning techniques to solve complex business problems.
• Technical & Platform Skills
• Proven experience with cloud-native ML tools: AWS SageMaker, Azure ML Studio, Google AI
• Platform.
• Familiarity with DevOps and orchestration tools: Docker, Git, Step Functions, Lambda,Google AI or similar
• Comfort working with BI/reporting layers, testing, and model performance dashboards.
• Mathematics and Statistics
• Linear algebra, Bayesian method, information theory, statistical inference, clustering, regression etc
• Collaborate with Generative AI and RPA teams to develop intelligent workflows
• Participate in rapid prototyping, technical reviews, and internal capability building
• NLP and Computer Vision
• Knowledge of Hugging Face Transformers, Spacy or similar NLP tools
• YoLO, Open CV or similar for Computer vision.

COMPETENCIES

• Personal Effectiveness
• Social Awareness
• Entrepreneurship
• Problem Solving & Analytical Thinking
• Planning & Decision Making
• Capability Building
• Strategic Orientation
• Stakeholder Focus
• Networking
• Execution & Results
• Teamwork & Interpersonal influence
• HR Process and Systems Management (Proficient)
• Change Management (Practitioner)
• Learning and Development Management (Proficient)
• Performance Reporting and Analytics (Practitioner)
• HR Compliance Management (Proficient)