You will get a custom production-ready AI-powered RAG system
Project details
Looking for a cutting-edge solution to streamline your information retrieval and decision-making process? I will design and implement a complete end-to-end advanced Retrieval-Augmented Generation (RAG) pipeline tailored to your specific needs. With expertise in advanced RAG techniques, including neural search and large-scale knowledge integration, I ensure that the pipeline is production-grade, scalable, and optimized for performance. Whether you're working with structured or unstructured data, I'll help you harness the power of AI to deliver reliable, contextually relevant outputs.
AI Algorithms
Large Language Model, Multimodal Large Language Model, Transformer ModelAI Applications
AI Chatbot, AI Mobile App Development, AI Text-to-Speech, AI-Enhanced Classification, AI-Generated Code, Conversational AI, Image Processing, Machine Translation, Natural Language Generation, Natural Language Understanding, Sentiment Analysis, Synthetic Data GenerationAI Development Language
PythonAI Tools
Azure OpenAI, Hugging Face, PyTorch, TensorFlow, Word2vecAI Models
BERT, ChatGPT, GPT-3, GPT-4, GPT-J, GPT-Neo, LLaMAWhat's included $2,500
These options are included with the project scope.
$2,500
- Delivery Time 30 days
- Number of Revisions 5
- AI Model Integration
- Database Integration
- Detailed Code Comments
- MLOps
- Model Deployment
- Model Documentation
- Model Monitoring
- Model Testing & Optimization
- Model Tuning
- Natural Language Processing
- NLP Tokenization
- Pre-Training
- Prompt Engineering
- Setup File
- Source Code
Frequently asked questions
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BP
Brijesh P.
Jun 3, 2025
ML Engineer
Sushant is an exceptional ML engineer - thoughtful in deconstructing the problem all the way to building a production-worthy application.
About Sushant
Machine Learning Engineer | RAG & LLM Specialist | AWS Expert
Beverly, United States - 12:56 pm local time
🏆 𝐊𝐞𝐲 𝐀𝐜𝐡𝐢𝐞𝐯𝐞𝐦𝐞𝐧𝐭𝐬:
✥ AI-Powered Job Search Platform: Led the development of Govskills.io, an AI-powered job search tool enhancing candidate experience through optimized retrieval and LLMs.
✥ Advanced RAG: Developed a RAG-based regulation explorer end-to-end, improving retrieval accuracy by 20%, ensuring reliable compliance answers in regulatory context.
✥ AI Research: Designed workflows to reduce hallucinations in LLMs, novel methods for text style transfer using LLMs, automated unit test generation using LLMs, etc.
✥ Cloud Engineering: Built AWS-based infrastructure with 100+ nodes, doubling throughput while achieving sub-second query latency.
💡 𝐓𝐞𝐜𝐡𝐧𝐢𝐜𝐚𝐥 𝐄𝐱𝐩𝐞𝐫𝐭𝐢𝐬𝐞:
► Generative AI & LLMs:
✥ Advanced Transformer Models, GPT, Llama, Mistral, and Vision-Language Models (BakLLaVA).
✥ Fine-Tuning: Specialized in LoRA, PEFT, QLoRA, and supervised training for domain-specific needs.
✥ Prompt Engineering: 30+ projects designing tailored prompts for GPT, Claude, and open-source models (Llama, Mistral).
✥ AI-Driven Search: Improved search systems with LLM assisted search and knowledge graph integrations.
► RAG Stack & Knowledge Systems:
✥ Tools: LangChain, Weaviate, Pinecone, Chroma, Knowledge Graphs.
✥ Experience building end-to-end RAG applications, from frontend development to ML infrastructure.
✥ Expertise in context-aware retrieval systems, re-ranking techniques, embedding finetuning, RAG evaluation, etc.
► NLP & AI Applications:
✥ BERT/RoBERTa
✥ Text classification
✥ Text Style Transfer
✥ Sentiment analysis
► Cloud & Dev/MLOps:
✥ Infrastructure: Deep expertise in AWS (EC2, S3, Lambda, CloudFormation), Docker, Kubernetes, and building robust CI/CD pipelines for seamless deployment and scaling of AI applications.
✥ Automation: Proficient in using Terraform and Ansible for infrastructure as code, ensuring consistent and efficient deployment workflows.
✥ Monitoring & Optimization: Skilled in integrating tools like Prometheus, Grafana, and CloudWatch to monitor system performance and ensure uptime for mission-critical applications.
💼 𝐏𝐫𝐨𝐟𝐞𝐬𝐬𝐢𝐨𝐧𝐚𝐥 𝐄𝐱𝐩𝐞𝐫𝐢𝐞𝐧𝐜𝐞:
► Machine Learning Engineer | Citizen Codex LLC:
✥ Led advanced research on hallucination mitigation for LLMs in regulatory AI.
✥ Designed RAG systems with vector databases and knowledge graphs to enhance retrieval precision.
✥ Developed Govskills.io, an AI-powered platform for federal job searches, boosting user satisfaction by automating resume compliance analysis.
► Machine Learning Engineer Intern | Lamini
✥ Conducted research on LLM unit test generation for C codebases, improving test pass rates by 30%.
✥ Automated feedback loops in model fine-tuning, reducing training cycles.
► Tech Lead & SRE | Minma, Inc.
✥ Leader of a 24-person engineering team
✥ Doubled system throughput by deploying scalable AWS infrastructures.
✥ Reduced query latency by 80% through caching and Elasticsearch migration.
🌟 𝐖𝐡𝐲 𝐖𝐨𝐫𝐤 𝐖𝐢𝐭𝐡 𝐌𝐞?
I deliver solutions that blend technical excellence with real-world impact. Whether it’s designing scalable architectures, improving AI reliability, or crafting custom LLMs, I’ll ensure your project’s success through transparent communication and a results-oriented approach.
Steps for completing your project
After purchasing the project, send requirements so Sushant can start the project.
Delivery time starts when Sushant receives requirements from you.
Sushant works on your project following the steps below.
Revisions may occur after the delivery date.
Requirement Gathering
We'll discuss your use case, goals, and data sources to align on the project's scope and technical requirements.
Pipeline Design
I will design a custom RAG architecture, including retrievers, data pre-processing, and integration with a generative AI model.