PineQ Lab Technology
Machine Learning Engineer with Sagemaker and Bedrock Exp
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Machine Learning Engineer with 10+ years of experience, including 5+ in ML Engineering. Requires expertise in Amazon SageMaker, Generative AI with Bedrock, Python, and ML libraries, along with knowledge of RAG architecture and vector databases.
🌎 - Country
United States
💱 - Currency
$ USD
-
💰 - Day rate
Unknown
-
🗓️ - Date
August 1, 2026
🕒 - Duration
Unknown
-
🏝️ - Location
Unknown
-
📄 - Contract
Unknown
-
🔒 - Security
Unknown
-
📍 - Location detailed
Malvern, PA
-
🧠 - Skills detailed
#Hugging Face #ML (Machine Learning) #Docker #Transformers #PyTorch #SageMaker #Lambda (AWS Lambda) #NLP (Natural Language Processing) #Model Evaluation #Deep Learning #Cloud #API (Application Programming Interface) #"ETL (Extract #Transform #Load)" #GIT #Agile #S3 (Amazon Simple Storage Service) #Kubernetes #IAM (Identity and Access Management) #Libraries #OpenSearch #TensorFlow #Databases #AWS (Amazon Web Services) #AI (Artificial Intelligence) #Python
Role description
10+ years of overall experience and 5+ in Machine Learning Engineering or AI development.
Strong hands-on experience with Amazon SageMaker.
Experience building Generative AI applications using Amazon Bedrock.
Expertise in Python and ML libraries such as TensorFlow, PyTorch, Scikit-learn, Hugging Face Transformers.
Experience with prompt engineering, LLM orchestration, and AI agents.
Knowledge of Retrieval-Augmented Generation (RAG) architecture.
Experience with vector databases such as Pinecone, OpenSearch, FAISS, or Milvus.
Strong understanding of ML algorithms, deep learning, NLP, and model evaluation.
Experience with Docker, Kubernetes, and CI/CD pipelines.
Proficiency in AWS services including Lambda, S3, IAM, CloudWatch, API Gateway, ECS/EKS, and Step Functions.
Experience with Git and Agile development methodologies
10+ years of overall experience and 5+ in Machine Learning Engineering or AI development.
Strong hands-on experience with Amazon SageMaker.
Experience building Generative AI applications using Amazon Bedrock.
Expertise in Python and ML libraries such as TensorFlow, PyTorch, Scikit-learn, Hugging Face Transformers.
Experience with prompt engineering, LLM orchestration, and AI agents.
Knowledge of Retrieval-Augmented Generation (RAG) architecture.
Experience with vector databases such as Pinecone, OpenSearch, FAISS, or Milvus.
Strong understanding of ML algorithms, deep learning, NLP, and model evaluation.
Experience with Docker, Kubernetes, and CI/CD pipelines.
Proficiency in AWS services including Lambda, S3, IAM, CloudWatch, API Gateway, ECS/EKS, and Step Functions.
Experience with Git and Agile development methodologies
