Checkmate-posted 2 months ago
$100,000 - $140,000/Yr
Full-time • Mid Level

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.

  • Design and build next-generation ML models using advanced tools like PyTorch, Gemini, and Amazon SageMaker - primarily on Google Cloud or AWS platforms.
  • Build robust feature pipelines; extract, clean, and transform large-scale transactional and behavioral data.
  • 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.
  • Implement logging, monitoring, and alerting for model drift and data-quality issues; schedule retraining workflows.
  • Collaborate closely with data science, engineering, and product teams to define, explore, and implement solutions to open-ended problems.
  • Mentor junior engineers on best practices in ML engineering.
  • Produce clear documentation of model architecture, data schemas, and operational procedures.
  • Present findings to technical and non-technical stakeholders.
  • Bachelors/Master’s degree in Computer Science, Engineering, Statistics, or related field.
  • 5+ years of industry experience (or 1+ year post-PhD).
  • Proven experience shipping production-grade ML models and optimization systems.
  • Hands-on experience building and maintaining scalable backend systems and ML inference pipelines for real-time or batch prediction.
  • 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).
  • 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.
  • Solid understanding of regression metrics (MAE, RMSE, R²) and hyperparameter tuning.
  • Proven skills deploying ML solutions in AWS, GCP, or Azure; knowledge of Docker, Kubernetes, and CI/CD pipelines.
  • Excellent communication skills; ability to translate complex technical concepts into clear, actionable insights.
  • 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.
  • 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
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