10 Aug
|
Recognized
|
Hyderabad
10 Aug
Recognized
Hyderabad
About the Role
We are seeking a Senior AI Engineer to lead
a strategic enterprise engagement spanning Pricing Elasticity Modeling,
Customer Segmentation, and AI -driven Supply Chain Intelligence. You will deliver
production -grade ML/LLM solutions.
Requirements
Key Responsibilities
Pricing Elasticity Modeling
- Build econometric and ML models
for price elasticity across products, channels, and segments.
- Develop dynamic and competitive
pricing using regression, Bayesian, causal inference, and RL techniques.
- Create scenario simulation
tools to forecast revenue and margin impact of pricing strategies.
Customer Segmentation
- Develop behavioral, RFM,
lifecycle, and propensity -based segmentation using clustering and embeddings.
- Leverage LLMs to enrich
customer representations from unstructured data (reviews, tickets,
communications).
- Operationalize segments into
CRM, CDP, and personalization platforms for marketing and sales activation.
AI -Driven Supply Chain Intelligence
- Architect demand forecasting
using classical (ARIMA, Prophet) and deep learning (LSTM, TFT, N -BEATS)
methods.
- Build inventory optimization,
replenishment, and supplier risk models using ML and operations research.
- Design LLM -powered agents and
copilots for analytics, anomaly detection, and decision support.
Technical Leadership & Delivery
- Own end -to -end solution design
— data ingestion, feature engineering, deployment, monitoring, governance.
- Mentor data scientists/ML
engineers; lead code, model, and design reviews.
- Establish MLOps/LLMOps best
practices: CI/CD, versioning, drift detection, and responsible AI guardrails.
Required Qualifications
- 3+ years in AI/ML engineering
or applied data science, with 1+ year of production LLM experience.
- Bachelor's or Master's in CS,
Data Science, Statistics, OR, Economics, or related quantitative field.
- Robust Python skills with
scikit -learn, XGBoost/LightGBM,
and PyTorch or TensorFlow.
- Hands -on with LLM tooling:
LangChain/LlamaIndex, Hugging Face, OpenAI/Anthropic/Bedrock/Vertex APIs.
- Experience building RAG
systems, agentic workflows, and prompt engineering for enterprise use cases.
- Solid grounding in statistics,
time -series forecasting, and causal inference.
- Production deployment
experience on AWS (SageMaker), Azure ML, or GCP Vertex AI.
- Strong SQL and modern data
stack exposure: Snowflake, Databricks, BigQuery, or Redshift.
- MLOps experience with MLflow,
Airflow, Docker, Kubernetes, and CI/CD pipelines.
- Excellent stakeholder
communication; able to present to executive audiences.
Preferred Qualifications
- Domain experience in retail,
CPG, e -commerce, manufacturing, or logistics.
- Familiarity with vector DBs
(Pinecone, Weaviate, FAISS, pgvector), uplift modeling, and bandits.
- Cloud certifications: AWS ML
Specialty, Azure AI Engineer, or GCP ML Engineer.
- Prior consulting or
client -facing delivery leadership; OSS contributions or publications a plus.