Senior Python Engineer – Machine Learning & Data Analysis
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Senior Python Engineer – Machine Learning & Data Analysis, offering a contract length of "unknown" at a pay rate of "unknown". Key skills include Python, machine learning workflows, SQL, and cloud-based MLOps experience.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
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🗓️ - Date discovered
September 24, 2025
🕒 - Project duration
Unknown
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🏝️ - Location type
Unknown
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📄 - Contract type
Unknown
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🔒 - Security clearance
Unknown
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📍 - Location detailed
Snoqualmie, WA
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🧠 - Skills detailed
#Model Evaluation #"ETL (Extract #Transform #Load)" #Flask #AI (Artificial Intelligence) #Cloud #TensorFlow #Deep Learning #Synapse #Docker #ADF (Azure Data Factory) #Data Pipeline #Python #ML (Machine Learning) #PyTorch #SQL (Structured Query Language) #Azure Data Factory #NumPy #Azure #Pandas #Data Science #Datasets #Scala #Kubernetes #Data Analysis #FastAPI #Deployment
Role description
Key Responsibilities
• Design, develop, and deploy Python-based ML solutions for large-scale data analysis.
• Build ETL/data pipelines to process structured and unstructured datasets.
• Perform exploratory data analysis (EDA), feature engineering, and model evaluation.
• Collaborate with data scientists, analysts, and business teams to translate business problems into technical solutions.
• Optimize models for scalability, performance, and accuracy.
• Mentor junior engineers and review code for quality and best practices.
Required Skills & Experience
• Strong proficiency in Python (Pandas, NumPy, Scikit-learn, FastAPI/Flask).
• Experience with machine learning workflows: data preprocessing, model training, evaluation, and deployment preferably using Microsoft stack – Azure ML, Azure Data Factory, Synapse Analytics, and related Microsoft AI/ML tools.
• Knowledge of cloud-based MLOps practices.
• Strong SQL and data modelling skills.
• Experience with deep learning frameworks (PyTorch, TensorFlow) is nice to have.
• Knowledge of containerization (Docker, Kubernetes) is nice to have.
Key Responsibilities
• Design, develop, and deploy Python-based ML solutions for large-scale data analysis.
• Build ETL/data pipelines to process structured and unstructured datasets.
• Perform exploratory data analysis (EDA), feature engineering, and model evaluation.
• Collaborate with data scientists, analysts, and business teams to translate business problems into technical solutions.
• Optimize models for scalability, performance, and accuracy.
• Mentor junior engineers and review code for quality and best practices.
Required Skills & Experience
• Strong proficiency in Python (Pandas, NumPy, Scikit-learn, FastAPI/Flask).
• Experience with machine learning workflows: data preprocessing, model training, evaluation, and deployment preferably using Microsoft stack – Azure ML, Azure Data Factory, Synapse Analytics, and related Microsoft AI/ML tools.
• Knowledge of cloud-based MLOps practices.
• Strong SQL and data modelling skills.
• Experience with deep learning frameworks (PyTorch, TensorFlow) is nice to have.
• Knowledge of containerization (Docker, Kubernetes) is nice to have.
