Python Engineer - AI/ML & LLM Specialist

Neotechie; United States; Hybrid; USD 150,000 - 210,000; Full time

Job summary

Neotechie is seeking a hands-on Python Engineer with strong AI/ML, NLP and LLM expertise to design and deploy production-grade AI apps. You will build scalable LLM systems, RAG pipelines and end-to-end ML infrastructure for real-world business use.

You’ll fine-tune transformers, develop REST APIs with FastAPI/Flask, and collaborate with cross-functional teams to deliver robust AI solutions, aligning with model deployment and monitoring best practices.

Qualifications

• Hands-on Python AI/ML development with NLP and LLMs.
• Experience fine-tuning transformer models and RAG pipelines.
• Proficient in building scalable ML infra and MLOps workflows.
• Familiar with vector databases and model deployment.

Responsibilities

• Design and build NLP/LLM systems for chatbots, summarization, and semantic search.
• Fine-tune LLMs using LoRA, PEFT, RLHF and prompt engineering techniques.
• Build RAG pipelines with vector databases like Pinecone, Weaviate, ChromaDB, FAISS.
• Develop end-to-end ML pipelines: preprocessing, training, eval, deployment, monitoring.
• Optimize inference with quantization, pruning, batching and tuning.
• Create REST APIs and microservices with FastAPI or Flask.
• Collaborate with product/engineering/data teams to deliver scalable AI solutions.
• Maintain experiment tracking, model versioning, and MLOps workflows.
• Stay updated on emerging LLM tech and tooling.

Skills

Python

PyTorch

NLP

LLMs

Generative AI

Prompt Engineering

FastAPI

Flask

SQL

Pandas

NumPy

Machine Learning

Transformer Models

Semantic Search

Conversational AI

Education

Bachelor's degree in Computer Science, Engineering, Mathematics, or related field

Tools

Pinecone

Weaviate

ChromaDB

FAISS

MLflow

Weights & Biases

DVC

Spark

Ray

Dask

Job description

Seeking a hands-on Python Engineer with strong expertise in AI/ML, NLP, and Large Language Models (LLMs) to build and deploy production-grade AI applications. The role involves designing scalable LLM systems, developing RAG pipelines, fine-tuning transformer models, and building end-to-end ML infrastructure for real-world business applications.

Responsibilities

• Design and build AI/ML systems focused on NLP and LLM-powered applications such as chatbots, summarization, classification, semantic search, and entity extraction.
• Fine-tune and optimize LLMs including LLaMA, Mistral, GPT variants, and transformer-based models using LoRA, PEFT, RLHF, and prompt engineering techniques.
• Build and implement RAG (Retrieval-Augmented Generation) pipelines integrated with vector databases like Pinecone, Weaviate, ChromaDB, and FAISS.
• Develop scalable ML pipelines covering preprocessing, model training, evaluation, deployment, monitoring, and retraining.
• Optimize model inference using quantization, pruning, batching, and performance tuning techniques.
• Build REST APIs and microservices using FastAPI or Flask for AI model deployment.
• Collaborate with product, engineering, and data teams to deliver scalable AI solutions.
• Maintain experiment tracking, model versioning, and MLOps workflows.
• Stay updated with emerging LLM technologies, frameworks, and AI tooling.

Required Skills

• Python
• PyTorch
• NLP
• LLMs
• Generative AI
• Hugging Face
• LangChain
• LlamaIndex
• RAG Pipelines
• Prompt Engineering
• FastAPI
• Flask
• SQL
• Pandas
• NumPy
• Machine Learning
• Transformer Models
• Model Deployment
• Semantic Search
• Conversational AI

Preferred Skills

• Experience with vector databases including Pinecone, Weaviate, ChromaDB, and FAISS.
• Familiarity with AWS SageMaker, GCP Vertex AI, or Azure ML.
• Experience with MLOps tools such as MLflow, Weights Biases, and DVC.
• Knowledge of distributed computing frameworks like Spark, Ray, or Dask.
• Understanding of quantization, pruning, distillation, and inference optimization techniques.
• Contributions to open-source AI/ML projects are a plus.
• Education: Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field. Equivalent practical experience, open-source work, or self-driven AI/ML projects will also be considered.

Disclaimer: This job posting and Location has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.