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Associate Manager - AI & ML - 13512

5 - 8 years

0 Lacs

Hyderabad Telangana India

Posted:3 days ago| Platform: Linkedin logo

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Skills Required

ai ml learning analytics model automation reporting development reinforcement forecasting pricing design inference architecture azure openai data engineering training evaluation deployment drift aws gcp sagemaker api etl integration power kafka apache airflow compliance consulting management service finance procurement programming python sql tensorflow xgboost devops orchestration docker git layers testing mathematics algebra clustering regression prototyping effectiveness entrepreneurship planning networking teamwork

Work Mode

On-site

Job Type

Full Time

Job Description

Job Purpose

Manage Electro-mechanical and Fire & Safety operations to ensure the quality and deliverables in a timely and cost effective manner at all office locations of Bangalore;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

Key Accountabilities

Accountabilities Key Performance IndicatorsAI & 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 — 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 providerIT Service Providers / Analyst FirmsVendors

INTERNAL INTERACTIONS

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

FINANCIAL DIMENSIONS

Other Dimensions

EDUCATION QUALIFICATIONS

  • Engineering

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

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