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Senior Machine Learning Engineer

Headsmart Solutions

5 - 10 years

Hyderabad

Posted: 21/03/2026

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Job Description

Job Description: Senior Machine Learning Engineer

Experience: 68 years

Employment Type: Full-time

Location: Hyderabad

Role Summary

We are seeking a Senior Machine Learning Engineer to design and build intelligent

decision-making systems using time-series forecasting, spatial modeling, and optimization

techniques. The role involves evolving systems from rule-based logic to advanced ML and

reinforcement learning, and deploying them at production scale.

Key Responsibilities

Build time-series demand forecasting models using rolling statistics, classical ML, and

deep learning

Develop spatial / geospatial models using hexagonal or grid-based representations

(e.g., H3)

Implement classification models (e.g., logistic regression, tree-based models) for risk

and state detection

Design and optimize scoring and ranking engines using weighted heuristics and

learned value functions

Work on policy learning and reinforcement learning for long-horizon optimization

Own feature engineering, training pipelines, and model evaluation Deploy

models for batch and near-real-time inference Implement model monitoring, drift detection, and retraining workflows

Collaborate closely with data engineering and backend teams to productionize ML

systems

Required Skills & Experience

78 years of hands-on experience in Machine Learning / Applied

AI Strong proficiency in Python and SQL, FastAPI

Solid understanding of time-series forecasting techniques

Experience with classification, regression, and ranking models Practical

experience with tree-based models (XGBoost, LightGBM, Random Forest)

Experience designing production ML pipelines

Strong understanding of feature engineering, model evaluation, and explainability

Good to Have

Experience with spatio-temporal models (ST-GNNs, Transformers, temporal CNNs)

Exposure to Reinforcement Learning, contextual bandits, or MDP-based systems

Experience with graph-based modeling

Familiarity with MLflow, feature stores, Kubernetes

Experience working with large-scale, high-frequency data systems

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