Senior Machine Learning Engineer

October 20

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ItsaCheckmate

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SaaS • Hospitality

ItsaCheckmate is a technology company that provides powerful ordering solutions for busy restaurants. Their platform enables restaurants to drive sales and connect with customers through various ordering channels, including web, app, kiosk, and third-party integrations. With its scalable enterprise technology, ItsaCheckmate helps restaurants manage and streamline operations, reduce order errors, and increase productivity. They offer features such as loyalty programs, catering management, QR-code ordering, and unified channel management. Trusted by over 2,400 brands, ItsaCheckmate is dedicated to supporting restaurant growth with innovative digital solutions and a marketplace of integrations.

201 - 500 employees

☁️ SaaS

📋 Description

• Model Development: Design and build next-generation ML models using advanced tools like PyTorch, Gemini, and Amazon SageMaker - primarily on Google Cloud or AWS platforms. • Feature Engineering: Build robust feature pipelines; extract, clean, and transform large-scale transactional and behavioral data. Engineer features like time-based attributes, aggregated order metrics, categorical encodings (LabelEncoder, frequency encoding). • Experimentation & Evaluation: Define metrics, run A/B tests, conduct cross-validation, and analyze model performance to guide iterative improvements. Train and tune regression models (XGBoost, LightGBM, scikit-learn, TensorFlow/Keras) to minimize MAE/RMSE and maximize R². • Own the entire modeling lifecycle end-to-end, including feature creation, model development, testing, experimentation, monitoring, explainability, and model maintenance. • Monitoring & Maintenance: Implement logging, monitoring, and alerting for model drift and data-quality issues; schedule retraining workflows. • Collaboration & Mentorship: Collaborate closely with data science, engineering, and product teams to define, explore, and implement solutions to open-ended problems that advance the capabilities and applications of Checkmate, mentor junior engineers on best practices in ML engineering. • Documentation & Communication: Produce clear documentation of model architecture, data schemas, and operational procedures; present findings to technical and non-technical stakeholders.

🎯 Requirements

• Academics: Bachelors/Master’s degree in Computer Science, Engineering, Statistics, or related field • Experience: • - 5+ years of industry experience (or 1+ year post-PhD). • - Building and deploying advanced machine learning models that drive business impact • - Proven experience shipping production-grade ML models and optimization systems, including expertise in experimentation and evaluation techniques. • - Hands-on experience building and maintaining scalable backend systems and ML inference pipelines for real-time or batch prediction • Programming & Tools: • - Proficient in Python and libraries such as pandas, NumPy, scikit-learn; familiarity with TensorFlow or PyTorch. • - Hands-on with at least one cloud ML platform (AWS SageMaker, Google Vertex AI, or Azure ML). • Data Engineering: • - Hands-on experience with SQL and NoSQL databases; comfortable working with Spark or similar distributed frameworks. • - Strong foundation in statistics, probability, and ML algorithms like XGBoost/LightGBM; ability to interpret model outputs and optimize for business metrics. • - Experience with categorical encoding strategies and feature selection. • - Solid understanding of regression metrics (MAE, RMSE, R²) and hyperparameter tuning. • Cloud & DevOps: Proven skills deploying ML solutions in AWS, GCP, or Azure; knowledge of Docker, Kubernetes, and CI/CD pipelines • Collaboration: Excellent communication skills; ability to translate complex technical concepts into clear, actionable insights. • Working Terms: Candidates must be flexible and work during US hours at least until 6 p.m. ET in the USA, which is essential for this role & must also have their own system/work setup for remote work.

🏖️ Benefits

• Health Care Plan (Medical, Dental & Vision) • Retirement Plan (401k) • Life Insurance (Basic, Voluntary & AD&D) • Flexible Paid Time Off • Family Leave (Maternity, Paternity) • Short Term & Long Term Disability • Training & Development • Work From Home • Stock Option Plan