Compunnel Inc.

Machine Learning Engineer

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Machine Learning Engineer on a contract basis, hybrid in Smithfield, RI or Westlake, TX. Pay rate is competitive. Requires 5+ years of experience, strong Python and Java skills, and expertise in Generative AI and AWS services.
🌎 - Country
United States
πŸ’± - Currency
$ USD
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πŸ’° - Day rate
Unknown
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πŸ—“οΈ - Date
October 14, 2025
πŸ•’ - Duration
Unknown
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🏝️ - Location
Hybrid
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πŸ“„ - Contract
Unknown
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πŸ”’ - Security
Unknown
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πŸ“ - Location detailed
Dallas, TX
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🧠 - Skills detailed
#Flask #FastAPI #Java #Data Pipeline #Scala #ML (Machine Learning) #Data Science #RDS (Amazon Relational Database Service) #Deep Learning #API (Application Programming Interface) #Langchain #Cloud #Deployment #Model Deployment #AI (Artificial Intelligence) #Snowflake #SageMaker #AWS (Amazon Web Services) #Python #Automation #Agile #AWS SageMaker #Programming #Computer Science #"ETL (Extract #Transform #Load)" #EC2
Role description
Job Title: Machine Learning Engineer Location: Smithfield, RI or Westlake, TX (Hybrid) Contract Type: Contract Position Overview We are seeking a Machine Learning Engineer to design, implement, and enhance technical solutions for Generative AI (Gen AI) initiatives. The role involves developing RAG pipelines, prompt engineering, fine-tuning models, creating data pipelines, and building APIs for ML model integration. You will collaborate closely with data scientists and software engineers to deploy scalable AI solutions in the cloud. Key Responsibilities β€’ Design, develop, and deploy machine learning and deep learning systems using modern ML algorithms and frameworks. β€’ Build and maintain APIs for ML model integration using FastAPI or Flask. β€’ Develop and optimize Generative AI solutions leveraging LLMs, LangChain, LlamaIndex, Prompt Engineering, and Fine Tuning. β€’ Collaborate with data scientists to train, retrain, and evaluate models to improve performance. β€’ Implement and manage data pipelines, cloud hosting, and API development for production-grade AI systems. β€’ Deploy and monitor ML models using AWS SageMaker, EC2/EKS, and cloud data platforms such as Snowflake or RDS. β€’ Conduct experiments, run machine learning tests, and document results to continuously enhance AI performance. Required Skills and Experience β€’ 5+ years of hands-on experience as a Machine Learning Engineer or similar role. β€’ Strong programming skills in Python and Java. β€’ Proven expertise in Prompt Engineering and application of Generative AI techniques in real-world scenarios. β€’ Experience building APIs and backend services using FastAPI or Flask. β€’ Solid understanding of ML lifecycle management, from data preprocessing to model deployment. β€’ Hands-on experience with AWS services β€” particularly SageMaker, EC2, EKS, and cloud data tools like Snowflake. β€’ Strong foundation in data science, model training, and performance optimization. β€’ Bachelor’s degree in Computer Science, Data Science, or a related technical field (or equivalent experience). About the Team You’ll be part of an agile AI delivery engineering team focused on building next-generation AI-powered solutions. The team works on developing innovative and scalable products that drive automation and business transformation using cutting-edge cloud and AI technologies.