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AI/ML Engineer

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Onsite

AI/ML Engineer

DARE TO DREAM

AI/ML Engineer

Skills

SQL QueriesData EngineeringPythonData VisualizationDatabricksData AnalysisMachine LearningAIPySparkAzure

5 days ago

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Important information


Contract type:

Freelance / Contract

Salary:

$70 – $80 / hour

Location:

Diamond Bar, CA, USA

Work mode:

Onsite

Published on:

16 October 2026

What they need


Job Summary

Strong experience with Computer Vision and DatabricksJob Description: Senior Data Scientist / ML Engineer

  • Location: Diamond Bar, CA (Onsite)
  • Work Mode: Onsite (Full-Time Contract)
  • Budget: $70 hr on C2C
  • Experience Range: 4 - 6 Years

**Position Overview:**We are looking for a Senior Data Science and Machine Learning resource who has strong hands-on experience in building, scaling, and deploying AI models. The ideal candidate will work closely within the Azure Databricks ecosystem and implement both traditional Machine Learning pipelines and modern AI solutions (including Computer Vision and Generative AI).Core Technical Skills Needed:

  • Azure Databricks Stack: Hands-on experience with Databricks Workspace, PySpark, MLflow, Delta Lake, and Azure cloud data services.
  • Core Languages: Strong proficiency in Python, SQL, statistical analysis, and data visualization.
  • AI**/*ML** Models:* Experience developing and deploying machine learning models for real-world enterprise use cases.
  • Computer Vision: Experience with Vision-based AI algorithms, object detection, or image processing (e.g., YOLO, OpenCV).
  • Generative AI (Plus Point): Exposure to LLMs, RAG frameworks, Azure OpenAI, or prompt engineering is highly preferred.

Key Responsibilities:

  • Build, optimize, and deploy end-to-end Machine Learning lifecycles (MLOps) using Databricks and MLflow.
  • Perform advanced data engineering and data analysis using PySpark and SQL.
  • Collaborate with business and cross-functional technical teams to convert requirements into AI solutions.

Pay: $70.00 - $80.00 per hour

Expected hours: 40.0 per week

Work Location: In person

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