Machine Learning Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Machine Learning Engineer in Malvern, PA, offering a contract length of "unknown" and a pay rate of "unknown." Key skills include AWS services, Python, SQL, deep learning, MLOps, and data engineering expertise.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
-
🗓️ - Date discovered
August 21, 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
#Deep Learning #Data Engineering #Monitoring #Supervised Learning #Lambda (AWS Lambda) #PyTorch #SQL (Structured Query Language) #AWS (Amazon Web Services) #Python #PySpark #Data Lake #BERT #Programming #Deployment #ML (Machine Learning) #FastAPI #Docker #TensorFlow #Athena #Spark (Apache Spark) #Model Deployment #MLflow #SageMaker #EC2 #AI (Artificial Intelligence) #Scala #Data Pipeline #Unsupervised Learning #Redshift
Role description
Title: Machine Learning Engineer
Location: Malvern,PA
Job Description:
Qualifications
• 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 housearchitectures
Title: Machine Learning Engineer
Location: Malvern,PA
Job Description:
Qualifications
• 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 housearchitectures
