Senior Machine Learning Engineer (Core Modelling) — 5+ yrs

Indpro AB; Bengaluru; On-site; INR 1,800,000 - 3,200,000; Full time

Job summary

Indpro AB in Bengaluru, India, is seeking a Senior Machine Learning Engineer to own complex ML problems from ideation to production deployment. You will design robust feature pipelines and validation strategies, and set the team’s evaluation standards with statistical rigor.

The role emphasizes owning the technical quality bar, mentoring peers, and collaborating with product stakeholders to frame problems accurately. Strong grounding in statistics and Python is essential.

Qualifications

• 5+ years hands-on building and shipping production ML models with measurable business impact
• Strong foundations in statistics, probability, and experimental design
• Excellent Python (scikit-learn, PyTorch and/or TensorFlow), strong SQL, solid data engineering fundamentals
• Demonstrated judgment on leakage prevention, calibration, class imbalance, and metric selection
• Practical depth in at least two of: tree ensembles, deep learning, probabilistic models, time-series forecasting
• Experience reviewing or mentoring other engineers' modelling work

Responsibilities

• Own complex ML problems end-to-end, from ambiguous business questions to production deployment
• Design feature engineering pipelines and validation strategy for non-trivial leakage risk
• Set and review evaluation methodology for the team — metric selection, experiment design, statistical validity
• Lead retraining/drift-monitoring strategy for models you and others ship
• Use GenAI selectively where it improves the solution, not as a substitute for modelling
• Partner directly with product/business stakeholders to frame problems correctly

Skills

Python (scikit-learn/PyTorch/TF)

SQL

Statistics & experimental design

Production ML engineering

Mentoring/leadership

Model evaluation & leakage prevention

Tools

scikit-learn

PyTorch

TensorFlow

XGBoost/LightGBM/CatBoost

SQL tooling

Job description

Build models that matter — and set the bar for how we build them.

At INDPRO., we build machine learning systems that make real decisions in production — from forecasting and anomaly detection to ranking, classification, and probabilistic modelling. Our models power products, customers, and business outcomes.

We're looking for a Senior Machine Learning Engineer who not only builds strong models independently but also raises the technical bar for the team — through design reviews, mentoring, and setting standards for evaluation and validation rigor.

About the Role

This is a core machine learning role — not a Prompt Engineering or RAG engineering position. We use LLMs and GenAI where they add value, but this role is about training, evaluating, and deploying robust ML models, and about owning the technical quality bar for how the team does it.

What You’ll Do

• Own complex ML problems end-to-end, from ambiguous business questions to production deployment
• Design feature engineering pipelines and validation strategy for problems with non-trivial leakage risk (time-series, panel data, multi-entity systems)
• Set and review evaluation methodology for the team — metric selection, experiment design, statistical validity
• Lead retraining/drift-monitoring strategy for models you and others ship
• Use GenAI selectively where it improves the solution, not as a substitute for modelling
• Partner directly with product/business stakeholders to frame problems correctly

What We’re Looking For

• 5+ years hands-on building and shipping production ML models with measurable business impact
• Strong foundations in statistics, probability, and experimental design
• Excellent Python (scikit-learn, PyTorch and/or TensorFlow), strong SQL, solid data engineering fundamentals
• Demonstrated judgment on leakage prevention, calibration, class imbalance, and metric selection — ideally with examples you can walk through
• Practical depth in at least two of: tree ensembles (XGBoost/LightGBM/CatBoost), deep learning (CNNs/LSTMs/Transformers), probabilistic models, time-series forecasting
• Experience reviewing or mentoring other engineers' modelling work

Nice to Have

Bayesian/probabilistic modelling, advanced forecasting systems, LoRA/PEFT/fine-tuning, production MLOps & CI/CD, Kaggle/OSS/publications.

Not This Role

Prompt engineering, RAG pipeline development, agent orchestration (LangChain/LangGraph/CrewAI) as a primary skill, or building on top of third-party LLM APIs without training/evaluating ML models.