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Senior Machine Learning Engineer at Checkmate. Location Information: USA. We’re seeking a Mid-Level Machine Learning Engineer to join our growing Data Science & Engineering team. In this role, you will design, develop, and deploy ML models that power our cutting-edge technologies like voice ordering, prediction algorithms, and customer-facing analytics. You’ll collaborate closely with data engineers, backend engineers, and product managers to take models from prototyping through to production, continuously improving accuracy, scalability, and maintainability. . . Essential Job Functions . • 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. . 100 % Remote. $100,000 to $140,000. 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. . Preferred Qualifications . Master’s or advanced degree in Computer Science, Engineering, Statistics, or related field. . Familiarity with data-privacy regulations (GDPR, CCPA) and best practices in secure ML. . Open-source contributions or publications in ML/AI conferences. . Experience with Ruby on Rails programming framework. . 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. . About the company. Checkmate empowers enterprise restaurant brands with powerful ordering solutions and hands-on support. Our scalable technology enables restaurants to drive sales across channels, including custom websites, apps, kiosks, catering, third-party marketplaces, voice AI, and more. With seamless integrations, smarter analytics, and 24/7 service, Checkmate helps brands conquer their digital goals. Restaurants can launch unique ordering experiences, centrally manage menus, recapture revenue, leverage customer data, and continually adapt with new integrations.. We believe a thoughtful blend of technology and hands-on support leads to better restaurant outcomes. Our vision is to provide this combination of software and service to every brand so they can scale their digital business with less effort. Looking ahead, our team is not only focused on solving today's problems but on anticipating and addressing tomorrow's challenges. Through our partnership with restaurants, we aim to help expand their digital footprint and build stronger connections with their customers.