Overview
On Site
Contract - W2
Contract - 12
Skills
Gen AI
Job Details
Hello
Title : GEN AI Engineer
Contract : 12+ Months
Location : 5 days onsite in McLean, VA
Job Description :
- A GenAI Engineer in the US builds and deploys generative AI applications, models, and systems that create new content like text, images, or code. Responsibilities include fine-tuning large language models (LLMs), developing retrieval-augmented generation (RAG) pipelines, integrating vector databases, and working with cloud-based GenAI services.
- They often use frameworks such as LangChain, collaborate with cross-functional teams, and ensure the responsible deployment of AI solutions across various industries.
Required Skills :
- Model Development & Deployment: Design, develop, and deploy generative AI models and applications.
- LLM Optimization: Fine-tune and evaluate Large Language Models (LLMs) for performance and efficiency.
- Content Creation: Create new content such as text, images, and code using GenAI techniques like GANs or LLMs.
- RAG Pipeline Development: Build and integrate retrieval-augmented generation (RAG) pipelines with vector databases like Pinecone or FAISS.
- Prompt Engineering: Craft and optimize prompts for LLM-based applications.
- Data Preprocessing: Preprocess unstructured data (text, images, etc.) for LLM consumption.
- Cloud Integration: Integrate GenAI services from cloud platforms like AWS Bedrock, Azure OpenAI, or Google Cloud Vertex AI.
- Collaboration: Work with senior engineers, data scientists, and cross-functional teams to deliver solutions.
- Code Reviews & Documentation: Participate in code reviews and maintain documentation for GenAI models and applications.
- Troubleshooting: Identify and resolve issues related to generative AI models and implementations.
Essential Skills
- Programming: Strong software engineering skills, particularly in Python.
- Frameworks: Experience with GenAI frameworks like LangChain, LangGraph, or AutoGen.
- Cloud Platforms: Familiarity with cloud platforms such as AWS, Azure, or Google Cloud Platform.
- MLOps: Knowledge of MLOps tools and best practices for managing the AI lifecycle.
- APIs: Experience in developing and using APIs for model integration.
- Problem-Solving: Ability to solve ambiguous problems and navigate complex challenges
Thanks and Regards,
Naveen
US IT Recruiter
Conch Technologies Inc,
.
Direct:
Email:
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