We're Hiring: Principal Consultant — AI & ML Solutions, 8–12 Years Experience ONLY

Aarvian is looking for a technically senior (not organisationally senior) Data Scientist who still lives in the code. This is a 60% hands-on / 40% technical leadership role — not a management position.

Please read before applying: This role requires 8 to 12 years of hands-on data science / ML engineering experience, with models personally built and deployed at production scale. If you have less than 8 years, or your experience is primarily people-management, dashboards, or stakeholder work without shipping production code — this is not the right fit, and your application won't be shortlisted. Please don't apply outside this range.

What You'll Do

- Design & build production ML/AI models end-to-end — data pipelines, feature engineering, training, evaluation, serving, monitoring (not POCs, not notebooks)
- Advanced ML: XGBoost, LightGBM, CatBoost, Random Forest — plus ensemble methods, causal models, or uplift modelling where needed
- Build Agentic AI systems: multi-agent workflows, RAG pipelines, LLM-powered business process automation (LangChain, LlamaIndex, simplAI, AutoGen)
- Own retail use cases: demand forecasting, markdown/price optimisation, promotional uplift, inventory intelligence, customer segmentation
- Act as the quality gate — review architectures, approve model designs, mentor by pairing (not lecturing)




- Be the technical bridge between the delivery team and the AI/ML CoE owner

Must-Haves
- 8–12 years in data science / ML engineering, career spent close to the code
- Models YOU personally built and deployed running at real production scale (not a 6-week pilot)
- Strong hands-on with XGBoost/LightGBM/Random Forest — hyperparameter tuning, SHAP explainability, class imbalance
- Expert Python (modular, testable, production-quality) and advanced SQL
- Real Agentic AI exposure — a production or near-production multi-agent/RAG/LLM-orchestrated system (chatbot/FAQ-bot experience does not count)
- PySpark/Databricks or equivalent; MLOps fundamentals (MLflow, drift monitoring, CI/CD for ML)
- Comfortable with startup pace, ambiguity, and full ownership

Positive to Have
- Retail/FMCG/e-commerce/CPG domain experience (demand forecasting, pricing, inventory)

Not a Fit If
- Your last 12 months has been mostly stakeholder management, dashboards, or team management without personally shipping code
- Your "deployed" models were pilots or notebooks handed off to someone else
- Your AI experience is primarily chatbot/virtual assistant development

Why Aarvian Real retail problems, real production impact. Direct access to the AI/ML CoE owner. Genuinely hard, interesting technical work — not the same use case recycled for different logos.

📌 Principal consultant-AI/ML Solutions (Bengaluru)
🏢 Aarvian
📍 Bengaluru