Python Engineer - Machine Learning & Data Analysis
@ ISoftTek Solutions Inc

Snoqualmie, Washington, United States
$130,000
On Site
Full Time
Posted 1 day ago

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XXXXXXXXXX XXXXXXXXX XXXXXXXX******* @isofttek.com
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Job Details

About the Role

The Python Engineer - Machine Learning & Data Analysis is a senior role based in Snoqualmie, WA. The successful candidate will design, develop, and deploy Python-based ML solutions for large-scale data analysis and build ETL/data pipelines to process both structured and unstructured datasets.

Key Responsibilities

  • Design, develop, and deploy Python-based machine learning solutions.
  • Build ETL/data pipelines for diverse datasets.
  • Perform exploratory data analysis, feature engineering, and model evaluation.
  • Collaborate with data scientists, analysts, and business teams.
  • Optimize models for scalability, performance, and accuracy.
  • Mentor junior engineers and review code for best practices.

Required Skills & Experience

  • Strong proficiency in Python (Pandas, NumPy, Scikit-learn, FastAPI/Flask).
  • Experience with ML workflows and Microsoft stack (Azure ML, Azure Data Factory, Synapse Analytics).
  • Knowledge of cloud-based MLOps practices.
  • Strong SQL and data modelling skills.
  • Familiarity with deep learning frameworks (PyTorch, TensorFlow) is a plus.
  • Experience with containerization (Docker, Kubernetes) is advantageous.

Key skills/competency

  • Python
  • Machine Learning
  • Data Analysis
  • ETL
  • EDA
  • Azure
  • SQL
  • Model Optimization
  • Code Review
  • Containerization
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How to Get Hired at ISoftTek Solutions Inc

🎯 Tips for Getting Hired

  • Research iSoftTek Solutions Inc's culture: Study mission, values, and recent news.
  • Customize your resume: Highlight Python and ML projects.
  • Emphasize technical skills: Include Azure and containerization experience.
  • Prepare for coding interviews: Practice Python and data analysis problems.

📝 Interview Preparation Advice

Technical Preparation

Review Python libraries and frameworks.
Study ML model deployment on Azure.
Practice building ETL pipelines.
Explore containerization and SQL optimization.

Behavioral Questions

Prepare collaboration examples with teams.
Describe past mentoring experiences.
Explain problem-solving under pressure.
Share decision-making in challenging projects.

Frequently Asked Questions