

AI + AWS Developer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an AI + AWS Developer on a 4–6 week contract, remote. Requires 3+ years in AWS (SageMaker, Lambda), ML/NLP deployment experience, and strong IaC skills (Terraform/CloudFormation). Competitive pay based on experience. Immediate start.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
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🗓️ - Date discovered
September 11, 2025
🕒 - Project duration
1 to 3 months
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🏝️ - Location type
Remote
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📄 - Contract type
Unknown
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🔒 - Security clearance
Unknown
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📍 - Location detailed
United States
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🧠 - Skills detailed
#Terraform #ML (Machine Learning) #Batch #Infrastructure as Code (IaC) #AI (Artificial Intelligence) #"ETL (Extract #Transform #Load)" #NLP (Natural Language Processing) #SageMaker #Scala #AutoScaling #Cloud #Deployment #Sentiment Analysis #AWS SageMaker #AWS (Amazon Web Services) #Documentation #Lambda (AWS Lambda)
Role description
Job Title: AI + AWS Developer (Contract Role)
Company: Jolly
Type: Contract (4–6 weeks)
Location: Remote
Start Date: Immediate
About Jolly
Jolly is an AI‑driven mental wellness platform helping organizations foster healthier, more resilient teams. We deliver personalized mindfulness exercises, mood‑based content recommendations, and proactive burnout alerts—powered by AWS ML services and scalable cloud infrastructure.
Role Overview
We need a hands‑on AWS & AI Engineer for a short‑term engagement (4–6 weeks) to implement and optimize key AI features on our production platform. You’ll work with our product and data‑science teams to deploy sentiment‑analysis pipelines, recommendation engines, and chatbot integrations using AWS SageMaker, Lex, and Personalize.
Key Responsibilities
• AI Feature Deployment
• Deploy and configure SageMaker endpoints for sentiment analysis and predictive models
• Integrate AWS Personalize for mood‑based content recommendations
• Extend Lex chatbot flows for guided break reminders and personalized coaching
• Infrastructure Configuration
• Provision or update IaC (Terraform/CloudFormation) for new AI‑service components
• Ensure low‑latency, auto‑scaling inference (Lambda / EKS or ECS)
• Testing & Optimization
• Load‑test model endpoints; tune instance types and batch settings
• Validate end‑to‑end workflows in staging before production rollout
• Documentation & Handoff
• Produce clear runbooks, architecture diagrams, and deployment guides
• Transfer knowledge to the core engineering team for ongoing maintenance
Required Qualifications
• 3+ years in AWS production environments, including SageMaker, Lambda, and Personalize
• Proven track record deploying ML/NLP models end‑to‑end
• Strong IaC skills with Terraform or CloudFormation
• Experience optimizing inference performance and cost
• Excellent collaboration and documentation skills
Contract Details
• Engagement: 4–6 weeks, full‑time (40 hrs/week)
• Location: Remote (US)
• Rate: Competitive, based on experience
• Start: ASAP
Job Title: AI + AWS Developer (Contract Role)
Company: Jolly
Type: Contract (4–6 weeks)
Location: Remote
Start Date: Immediate
About Jolly
Jolly is an AI‑driven mental wellness platform helping organizations foster healthier, more resilient teams. We deliver personalized mindfulness exercises, mood‑based content recommendations, and proactive burnout alerts—powered by AWS ML services and scalable cloud infrastructure.
Role Overview
We need a hands‑on AWS & AI Engineer for a short‑term engagement (4–6 weeks) to implement and optimize key AI features on our production platform. You’ll work with our product and data‑science teams to deploy sentiment‑analysis pipelines, recommendation engines, and chatbot integrations using AWS SageMaker, Lex, and Personalize.
Key Responsibilities
• AI Feature Deployment
• Deploy and configure SageMaker endpoints for sentiment analysis and predictive models
• Integrate AWS Personalize for mood‑based content recommendations
• Extend Lex chatbot flows for guided break reminders and personalized coaching
• Infrastructure Configuration
• Provision or update IaC (Terraform/CloudFormation) for new AI‑service components
• Ensure low‑latency, auto‑scaling inference (Lambda / EKS or ECS)
• Testing & Optimization
• Load‑test model endpoints; tune instance types and batch settings
• Validate end‑to‑end workflows in staging before production rollout
• Documentation & Handoff
• Produce clear runbooks, architecture diagrams, and deployment guides
• Transfer knowledge to the core engineering team for ongoing maintenance
Required Qualifications
• 3+ years in AWS production environments, including SageMaker, Lambda, and Personalize
• Proven track record deploying ML/NLP models end‑to‑end
• Strong IaC skills with Terraform or CloudFormation
• Experience optimizing inference performance and cost
• Excellent collaboration and documentation skills
Contract Details
• Engagement: 4–6 weeks, full‑time (40 hrs/week)
• Location: Remote (US)
• Rate: Competitive, based on experience
• Start: ASAP