Machine Learning Engineer- AWS
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Machine Learning Engineer- AWS in Malvern, PA, with a contract length of "unknown" and a pay rate of "unknown." Key skills include AWS services, Python, SQL, data engineering, and MLOps experience.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
-
🗓️ - Date discovered
September 13, 2025
🕒 - Project duration
Unknown
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🏝️ - Location type
On-site
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📄 - Contract type
Unknown
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🔒 - Security clearance
Unknown
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📍 - Location detailed
Malvern, PA
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🧠 - Skills detailed
#Monitoring #SageMaker #Lambda (AWS Lambda) #SQL (Structured Query Language) #Scala #PySpark #Data Engineering #Deep Learning #PyTorch #Deployment #Supervised Learning #Spark (Apache Spark) #Python #TensorFlow #Programming #EC2 #MLflow #Model Deployment #Athena #AWS (Amazon Web Services) #BERT #Data Lake #Docker #Unsupervised Learning #FastAPI #Redshift #ML (Machine Learning) #AI (Artificial Intelligence) #Data Pipeline
Role description
Role: Machine Learning Engineer- AWS
Location: Malevrn, PA
Job Description:
AWS Services: Proficiency in SageMaker, Glue, Lambda, EC2, EMR, Athena, Bedrock, and Redshift ML & AI
Expertise: Experience with supervised/unsupervised learning, deep learning (CNNs, RNNs), and LLMs (e.g., GPT, BERT, RAG, fine-tuning, LLMOps)
Programming: Strong in Python, SQL, PySpark; familiar with ML frameworks like Scikit-learn, TensorFlow, PyTorch
MLOps: Skilled in CI/CD, model deployment using MLflow, FastAPI, Docker, and monitoring pipelines
Data Engineering: Building scalable data pipelines, feature engineering, and data lake house architectures
Role: Machine Learning Engineer- AWS
Location: Malevrn, PA
Job Description:
AWS Services: Proficiency in SageMaker, Glue, Lambda, EC2, EMR, Athena, Bedrock, and Redshift ML & AI
Expertise: Experience with supervised/unsupervised learning, deep learning (CNNs, RNNs), and LLMs (e.g., GPT, BERT, RAG, fine-tuning, LLMOps)
Programming: Strong in Python, SQL, PySpark; familiar with ML frameworks like Scikit-learn, TensorFlow, PyTorch
MLOps: Skilled in CI/CD, model deployment using MLflow, FastAPI, Docker, and monitoring pipelines
Data Engineering: Building scalable data pipelines, feature engineering, and data lake house architectures
