Senior Machine Learning Engineer

Job not on LinkedIn

🕒 October 2

🇺🇸 United States – Remote

⏰ Full Time

🟠 Senior

🤖 Machine Learning Engineer

👻 Ghost score 10%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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DXS - Direct Expansion Solutions

WebsiteLinkedInAll Job Openings

51 - 200 employees

🏥 Healthcare

📦 Logistics

🏭 Manufacturing

Healthcare • Logistics • Manufacturing

DXS - Direct Expansion Solutions is a company that specializes in Variable Refrigerant Volume/Flow (VRV/VRF) air-source heat pumps and complementary technology and controls designed to reduce building energy use and emissions. They provide comprehensive solutions including system design, supply, commissioning, and service with a focus on inverter-based heat pumps and ventilation and indoor air quality systems. With offices across the United States and Canada, DXS offers expert knowledge in the application of air-source heat pump technology in various markets such as healthcare, residential, government, and military, aiming to decrease operating expenses and emissions through strategic electrification. They serve a range of clients, including engineers, architects, building owners, and contractors.

📋 Description

• Design, train, and evaluate models for prediction, ranking, and recommendation problems in order management • Contribute across problem framing, data preparation, feature engineering, training, evaluation, and retraining strategy • Translate product roadmap priorities into well-framed modeling problems with product management • Profile customer data, tune and validate models, and work with implementation and solution engineering teams • Build reproducible Python training pipelines and experiment tracking • Profile, clean, and validate large-scale enterprise SAP data • Package models and pipelines for deployment • Define production monitoring, including drift detection, performance regression signals, and data quality checks • Translate model behavior and operational reality when production issues arise • Integrate model output into the product stack through documented service interfaces • Apply responsible AI practices, including bias evaluation, explainability, and careful data handling • Document models and explain behavior, limitations, and trade-offs to engineers, delivery teams, sales, and customers • Review peers' modeling work and raise standards for rigor and reproducibility

🎯 Requirements

• Demonstrated depth in applied machine learning and data science, with models built that reached production and were measured there • Strong Python skills and fluency with PyTorch or TensorFlow, scikit-learn, pandas, and NumPy • Solid statistics foundation, including experimental design and appropriate evaluation metrics • Strong SQL and comfort working with large relational datasets • Experience building scheduled data and feature pipelines that work with messy source systems • Experience packaging, documenting, and specifying model requirements for a separate operations or platform team • Comfort working directly with customers and delivery teams • TypeScript or JavaScript proficiency sufficient to integrate with the product stack • Clear written and verbal communication • Bachelor's degree in Computer Science, Statistics, Mathematics, Engineering, or a related technical field, or equivalent practical experience • Resume must be uploaded in English

🏖️ Benefits

• Full-time contractor engagement • Equal-opportunity and affirmative-action employer • Equal employment opportunities regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status