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DXS - Direct Expansion Solutions
DXS - Direct Expansion Solutions
51 – 200 Employees
HealthcareLogisticsManufacturing
DXS - Direct Expansion Solutions delivers variable refrigerant volume and flow (VRV/VRF) air-source heat pump solutions for buildings across the United States and Canada. Its work spans system design, equipment supply, commissioning, service, inverter-based heat pumps, ventilation, and indoor air quality controls. DXS supports engineers, architects, building owners, and contractors in healthcare, residential, government, military, logistics, and manufacturing applications, helping clients pursue strategic electrification, lower energy use, reduced emissions, and more efficient building operations.
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Senior Machine Learning Engineer — Remote, United States

Lead production machine learning for DataXstream’s enterprise order management platform. Build recommendation, forecasting, propensity, and document intelligence models for customer use cases.

USUnited StatesRemoteFull-timeSeniorEnglish RequiredMachine Learning Engineer
JavaScriptNumpyPandasPythonPyTorchScikit-LearnSQLTensorflowTypeScript

Description

  • Develop, train, and assess prediction, ranking, and recommendation models for order management use cases
  • Support the full modeling lifecycle, from problem definition and data preparation through feature engineering, evaluation, and retraining
  • Partner with product management to convert roadmap priorities into clearly scoped machine learning problems
  • Analyze customer data, optimize and validate models, and collaborate with implementation and solutions engineering teams
  • Create reproducible Python training workflows with systematic experiment tracking
  • Prepare, cleanse, and validate large enterprise SAP datasets
  • Package trained models and pipelines for production deployment
  • Establish monitoring for model drift, performance degradation, and data quality issues
  • Diagnose production incidents by connecting model behavior with real-world operational conditions
  • Connect model predictions to the product platform through documented service interfaces
  • Use responsible AI methods covering bias assessment, explainability, and careful data governance
  • Record model designs and communicate behavior, limitations, and trade-offs to technical, delivery, sales, and customer audiences
  • Review colleagues’ modeling work and promote stronger standards for rigor and reproducibility

Requirements

  • Proven applied machine learning and data science expertise, including models deployed to production and evaluated with real-world measurements
  • Advanced Python capability and working fluency with PyTorch or TensorFlow, scikit-learn, pandas, and NumPy
  • Strong statistical foundation, including experimental design and selection of suitable evaluation metrics
  • Proficiency with SQL and experience handling large relational datasets
  • Experience developing scheduled data and feature pipelines across imperfect source systems
  • Experience packaging, documenting, and defining model requirements for an operations or platform team
  • Ability to work directly with customers and delivery stakeholders
  • TypeScript or JavaScript skills sufficient for integrating models with the product platform
  • Strong written and spoken communication skills
  • Bachelor’s degree in Computer Science, Statistics, Mathematics, Engineering, or a related technical discipline, or equivalent practical experience
  • English-language resume upload required

Benefits

  • Full-time contractor engagement
  • Employer committed to equal opportunity and affirmative action
  • Equal employment consideration regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or veteran status

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