

Excelon Solutions
Gen AI/ML Developer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Gen AI/ML Developer on a contract basis in Portland, Oregon. Key requirements include extensive AWS experience, proficiency in AI model development, and knowledge of governance best practices. Skills in AWS services and generative AI frameworks are essential.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
November 13, 2025
🕒 - Duration
Unknown
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🏝️ - Location
On-site
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
Portland, OR
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🧠 - Skills detailed
#Databases #Scala #Deployment #AI (Artificial Intelligence) #Cloud #Langchain #Security #Data Science #EC2 #Compliance #AWS (Amazon Web Services) #Lambda (AWS Lambda) #ML (Machine Learning) #SageMaker #S3 (Amazon Simple Storage Service)
Role description
Greetings,
This is Deepu from Excelon Solutions. Currently I'm looking for a best suited profile for the below requirement/s. Please review the JD and let me know your interest. Thanks.
Please share resume on deepu.kumar@excelonsolutions.com
Job Title: Gen AI/ML Developer
Hiring Mode: Contract -TP
Location: Portland, Oregon [ONSITE]
Note: We need core technical developer, Onsite Technical lead with strong AWS experience along with GenAI.
Job Description
AWS Bedrock
Anthropic Claude
LangChain
Vector Databases (e.g., Pinecone, Weaviate, Milvus, FAISS)
This position requires extensive AWS experience and strong technical expertise to design, build, and optimize Gen-AI solutions on cloud infrastructure. The role focuses on hands-on development, deployment, and integration of generative AI systems using modern frameworks and AWS services.
The Gen-AI space demands a unique combination of deep technical proficiency, AI model development skills, and a strong understanding of governance and security best practices.
Core Responsibilities:
• Design, develop, and deploy generative AI models and training pipelines leveraging AWS services (SageMaker, Lambda, EC2, S3, EKS, etc.).
• Build scalable AI architectures supporting multi-modal or large language model applications.
• Collaborate with cross-functional teams including data scientists, MLOps engineers, and cloud architects to deliver end-to-end Gen-AI solutions.
• Implement AI governance, security, and compliance measures within AWS environments.
• Optimize model performance, latency, and cost using best practices for distributed training and inference.
• Integrate AI solutions into enterprise applications, ensuring maintainability and scalability.
• Apply ethical AI principles and ensure responsible model development and deployment.
Greetings,
This is Deepu from Excelon Solutions. Currently I'm looking for a best suited profile for the below requirement/s. Please review the JD and let me know your interest. Thanks.
Please share resume on deepu.kumar@excelonsolutions.com
Job Title: Gen AI/ML Developer
Hiring Mode: Contract -TP
Location: Portland, Oregon [ONSITE]
Note: We need core technical developer, Onsite Technical lead with strong AWS experience along with GenAI.
Job Description
AWS Bedrock
Anthropic Claude
LangChain
Vector Databases (e.g., Pinecone, Weaviate, Milvus, FAISS)
This position requires extensive AWS experience and strong technical expertise to design, build, and optimize Gen-AI solutions on cloud infrastructure. The role focuses on hands-on development, deployment, and integration of generative AI systems using modern frameworks and AWS services.
The Gen-AI space demands a unique combination of deep technical proficiency, AI model development skills, and a strong understanding of governance and security best practices.
Core Responsibilities:
• Design, develop, and deploy generative AI models and training pipelines leveraging AWS services (SageMaker, Lambda, EC2, S3, EKS, etc.).
• Build scalable AI architectures supporting multi-modal or large language model applications.
• Collaborate with cross-functional teams including data scientists, MLOps engineers, and cloud architects to deliver end-to-end Gen-AI solutions.
• Implement AI governance, security, and compliance measures within AWS environments.
• Optimize model performance, latency, and cost using best practices for distributed training and inference.
• Integrate AI solutions into enterprise applications, ensuring maintainability and scalability.
• Apply ethical AI principles and ensure responsible model development and deployment.






