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Senior Machine Learning Engineer

1 hour, 36 minutes ago
India
Full-time
Senior
Machine Learning Engineer
Software Development
Apache Spark AWS CI/CD Docker GCP Kubernetes LightGBM NumPy Pandas Python PyTorch Ruby on Rails Scikit-learn SQL TensorFlow XGBoost
Apply Now
ItsaCheckmate

ItsaCheckmate

ItsaCheckmate simplifies digital orders and menu management for restaurants by integrating with various platforms directly into the POS, eliminating the need for tablets and manual transfers. Operators benefit from increased order volume, reduced error...

Hotels, Restaurants & Leisure
51-250
Founded 2016
$3M raised
View All Jobs 3

Description

  • Design, develop, and deploy machine learning models for voice ordering, prediction systems, and customer-facing analytics.
  • Build and maintain feature pipelines that extract, clean, and transform large-scale transactional and behavioral data.
  • Engineer time-based, aggregated, and categorical features to improve model performance.
  • Define evaluation metrics, run A/B tests, and perform cross-validation to measure and improve models.
  • Train, tune, and compare regression models to optimize business and technical performance.
  • Own the end-to-end modeling lifecycle, including feature creation, testing, monitoring, explainability, and maintenance.
  • Implement logging, monitoring, and alerting to detect model drift and data-quality issues.
  • Schedule and support retraining workflows for deployed models.
  • Collaborate with data science, engineering, and product teams to solve open-ended problems and move models from prototype to production.
  • Mentor junior engineers and produce documentation for model architecture, data schemas, and operational procedures.

Requirements

  • Bachelor’s or Master’s degree in Computer Science, Engineering, Statistics, or a related field.
  • 5+ years of industry experience, or 1+ year of experience post-PhD.
  • Experience building and deploying advanced machine learning models that drive business impact.
  • Proven experience shipping production-grade ML models and optimization systems.
  • Hands-on experience with scalable backend systems and ML inference pipelines for real-time or batch prediction.
  • Proficiency in Python and libraries such as pandas, NumPy, and scikit-learn.
  • Familiarity with TensorFlow or PyTorch.
  • Hands-on experience with at least one cloud ML platform such as AWS SageMaker, Google Vertex AI, or Azure ML.
  • Experience with SQL and NoSQL databases and distributed frameworks such as Spark.
  • Strong foundation in statistics, probability, and ML algorithms such as XGBoost and LightGBM.
  • Experience with categorical encoding strategies, feature selection, and hyperparameter tuning.
  • Solid understanding of regression metrics including MAE, RMSE, and R².
  • Proven ability to deploy ML solutions in AWS, GCP, or Azure.
  • Knowledge of Docker, Kubernetes, and CI/CD pipelines.
  • Excellent communication skills and ability to translate complex technical concepts into actionable insights.
  • Must be comfortable working US hours at least until 5 pm EST.
  • Preferred: Master’s or advanced degree in a related field.
  • Preferred: Familiarity with data privacy regulations such as GDPR and CCPA and secure ML best practices.
  • Preferred: Open-source contributions or publications in ML/AI conferences.
  • Preferred: Experience with the Ruby on Rails framework.

Interested in this position?

Apply directly on the company website

Apply Now

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