AI Engineer
Robotics Technologies LLC
Indianapolis, IN, United States
1 day ago
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Role details
Contract type
Temporary contract
Employment type
Full-time (> 32 hours)
Compensation
$172,640
Working hours
Regular working hours
Job source
Tech stack
LangGraph Framework
Artificial Intelligence
Amazon Web Services
Software Applications
Artificial Neural Networks
Microsoft Azure
Cloud Computing
Computer Programming
Continuous Integration
Information Extraction
Python (Programming Language)
Machine Learning
+26 more
OpenAI
Tensorflow
Sentiment Analysis
Unstructured Data
Pinecone
Google Cloud
Enterprise Software Applications
Pytorch
Retrieval-Augmented Generation
Large Language Models
Model Validation
Llamaindex
Generative AI
Agentic-AI
Git
Build Management
Scikit Learn
Kubernetes
Optimization Algorithms
HuggingFace
FAISS
Restful APIs
Document Classification
Docker
ChromaDB
Microservices
Job description
We are looking for an experienced AI Engineer to design, develop, and deploy intelligent applications using Artificial Intelligence, Machine Learning, and Generative AI technologies. The candidate will be responsible for building AI-powered solutions, developing predictive models, integrating large language models, and implementing scalable AI systems., * Design, develop, and implement AI-powered applications and intelligent automation solutions.
- Build and deploy machine learning models using Python and relevant AI frameworks.
- Develop Generative AI applications using Large Language Models (LLMs).
- Implement Retrieval-Augmented Generation (RAG) pipelines for enterprise applications.
- Work with OpenAI, Azure OpenAI, and Hugging Face models.
- Develop prompt engineering strategies to improve model accuracy and performance.
- Build AI agents using LangChain, LangGraph, and agent-based frameworks.
- Process and analyze structured and unstructured datasets.
- Develop NLP solutions for text classification, sentiment analysis, and information extraction.
- Integrate AI models with REST APIs and enterprise applications.
- Implement vector databases such as Pinecone, FAISS, and ChromaDB.
- Optimize model performance, scalability, and inference latency.
- Deploy AI solutions using Docker, Kubernetes, and cloud platforms.
- Monitor AI models and implement continuous improvement strategies.
- Collaborate with data scientists, software engineers, and business stakeholders.
Requirements
- Strong programming experience in Python.
- Hands-on experience with Machine Learning and Deep Learning.
- Knowledge of TensorFlow, PyTorch, and Scikit-learn.
- Experience with Generative AI and Large Language Models.
- Understanding of NLP and neural network architectures.
- Experience with LangChain, LangGraph, or LlamaIndex.
- Knowledge of RAG architecture and vector databases.
- Experience with REST APIs and microservices.
- Familiarity with AWS, Azure, or Google Cloud.
- Knowledge of Git, Docker, Kubernetes, and CI/CD pipelines.
- Understanding of model evaluation and optimization techniques.
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