

Data & AI - LLM Model Developer ( Only W2)
β - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data & AI - LLM Model Developer, offering a 6+ month W2 contract. Required skills include LLMs, NLPs, Deep Learning, and Python. Familiarity with cloud platforms and MLOps is essential, with nice-to-have skills in Springboot and AWS.
π - Country
United States
π± - Currency
$ USD
-
π° - Day rate
560
-
ποΈ - Date discovered
June 25, 2025
π - Project duration
More than 6 months
-
ποΈ - Location type
Remote
-
π - Contract type
W2 Contractor
-
π - Security clearance
Unknown
-
π - Location detailed
United States
-
π§ - Skills detailed
#Angular #Knowledge Graph #Azure #Langchain #ML (Machine Learning) #TensorFlow #NLP (Natural Language Processing) #AWS (Amazon Web Services) #AI (Artificial Intelligence) #PyTorch #Scala #ML Ops (Machine Learning Operations) #Transformers #API (Application Programming Interface) #Python #Databases #Hugging Face #Libraries #Deep Learning #"ETL (Extract #Transform #Load)" #Automation #Cloud #Programming
Role description
Heading 1
Heading 2
Heading 3
Heading 4
Heading 5
Heading 6
Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur.
Block quote
Ordered list
- Item 1
- Item 2
- Item 3
Unordered list
- Item A
- Item B
- Item C
Bold text
Emphasis
Superscript
Subscript
Data & AI - LLM Model Developer
Location: Hartford, 280 Trumbull, Corp (REMOTE)
6+ Months Contract
Only W2
β’ Must-have skills: LLMs, NLPs, Deep Learning, Machine Learning Operations, Python, RAG
Nice-to-have skills: Springboot, RESTful, AWS, Angular
β’ Job description:
1. Strong programming skills in Python with experience in LLM frameworks such as Hugging Face Transformers, OpenAI API, and LangChain.
1. Proficiency in deep learning libraries like TensorFlow or PyTorch, with expertise in fine-tuning, pre-training, and optimizing LLMs for real-world applications.
1. Hands-on experience with retrieval-augmented generation (RAG), agentic AI architectures, and LLM-based autonomous agents for decision-making and task automation.
1. Strong understanding of natural language processing (NLP) concepts, including embedding models, vector databases (FAISS, Pinecone, Weaviate), and knowledge graphs.
1. Familiarity with MLOps and experience working with cloud platforms (AWS or Azure) for scalable AI solutions.
1. Ability to design and implement LLM-powered AI agents that integrate with APIs, databases, and external systems to perform autonomous reasoning and multi-step workflows.
1. Experience in SpringBoot, RESTful Services, AWS, DB2, Openshift
1. Experience in Angular framework.