

Generative AI Engineer
β - Featured Role | Apply direct with Data Freelance Hub
This role is for a "Generative AI Engineer" on a 6+ month contract in Charlotte, NC, with a pay rate of $50-60/hr. Key skills include Python, TensorFlow, PyTorch, and experience with LLMs, SQL, and GCP.
π - Country
United States
π± - Currency
$ USD
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π° - Day rate
480
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ποΈ - Date discovered
June 27, 2025
π - Project duration
More than 6 months
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ποΈ - Location type
Hybrid
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π - Contract type
Unknown
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π - Security clearance
Unknown
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π - Location detailed
Charlotte, NC
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π§ - Skills detailed
#SQL (Structured Query Language) #AI (Artificial Intelligence) #BERT #Documentation #JavaScript #ML Ops (Machine Learning Operations) #Java #PyTorch #ML (Machine Learning) #MLflow #Scala #"ETL (Extract #Transform #Load)" #GCP (Google Cloud Platform) #NoSQL #Strategy #Langchain #Model Evaluation #Cloud #Python #TensorFlow #Agile #Datasets #Monitoring
Role description
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Job Title: AI Strategy & Solutions Lead
Duration: 6+ Month Contract
Address: Charlotte, NC
Pay Rate: $50-60/hr
Start Date: 7/21/2025
Duration of Assignment: 6 month contract (extensions possible not guaranteed)
Hours/Schedule/Training (as needed): Standard M-F, (hybrid - 3 days in/2 days remote)
Interview Process: 30 minute video interview
Job Description:
Lead complex initiatives including creation, implementation, documentation, validation, articulation, and defense of highly advanced AI and Generative AI solutions.
Deliver solutions for short and long-term objectives and provide analytical support for a wide array of business initiatives.
Utilize neural network architectures, including transformer-based models such as GPT, BERT, and others for driving operational efficiencies.
Familiarity with using diffusion models or multimodal AI depending on the use cases.
Hands-on experience with fine-tuning, training, and deploying large language models (LLMs) in on-premises, cloud, or hybrid environments.
Strong hold on tokenization, embeddings, and model evaluation metrics.
Present results of analysis, solution recommendations and AI-driven strategies for variety of business initiatives.
Experience:
Expertise in Python and key/major frameworks like TensorFlow, PyTorch, and HuggingFace.
Proficiency in LangChain and LangGraph in building LLM powered applications using LangChain for integrating external data and tools, and LangGraph for designing stateful, workflows (leveraging GraphDB) to automate complex processes
Experience in using ML Ops tools (e.g., MLflow, Kubeflow) for scaling and deploying models in production.
Experience working with on G Cloud Platform and expertise in using the GCP services.
Expertise in Scala for processing large-scale data sets for use cases.
Proficiency in Java, JavaScript (Node.js) for back-end integrations and for building interactive AI-based web applications or APIs.
Experience with SQL and NoSQL languages for managing structured, unstructured, and semi-structured data for AI and Generative AI applications.
Critical thinking and strong problem-solving skills.
Ability to learn the latest technologies and keep up with the trends in the Gen-AI space and apply to the business problems quickly.
Ability to multi-task and prioritize between projects and able to work independently and as part of a team.
Job Expectations:
Required to work individually or as part of a team on multiple AI and Generative AI projects and work closely with business partners across the organization.
Provide analytical support for developing, evaluating, implementing, monitoring, and executing models across business verticals using emerging technologies.
Expert knowledge on working on large datasets using SQL or NoSQL and present conclusions to key stakeholders.
Establish a consistent and collaborative framework with the business and act as a primary point of contact in delivering the solutions.
Experience in building quick prototypes to check feasibility and value to business.
Expert in developing and maintaining modular codebase for reusability.
Review and validate models and help improve the performance of the model under the preview of regulatory requirements.
Work closely with technology teams to deploy the models to production.
Prepare detailed documentations for projects for both internal and external use that comply with regulatory and internal audit requirements.
Strong understanding of Agile methodologies and enterprise software development.
Excellent communication and stakeholder management skills.