Python AI Developer (work-from-home)

Python AI Developer

Experience Required: 3 to 4 Years

Job Type: Full-Time

Department: Artificial Intelligence / Machine Learning

Reports To: CEO

Programming Languages

Key Responsibilities:

1. Design and implement scalable AI applications using Python, with a strong focus on LLM-based architectures.
2. Develop and fine-tune LLMs using frameworks such as Hugging Face Transformers, LangChain, or OpenAI APIs.
3. Build and deploy Retrieval-Augmented Generation (RAG) systems combining LLMs with vector databases and search tools.
4. Integrate LLMs into products and workflows via RESTful APIs and/or microservices.
5. Work with unstructured and semi-structured data (e.g., text, PDFs, web content) to build NLP pipelines.
6. Optimize model inference performance and reduce latency for real-time applications.
7. Collaborate with data scientists, backend engineers, and product managers to deliver high-impact solutions.
8. Stay up to date with the latest advancements in LLMs, RAG systems, and AI tooling.

9. Implemented Retrieval-Augmented Generation (RAG)

   to enable dynamic and context-aware responses in the conversational AI system.
10. Designed and developed Conversational AI chat functionality, leveraging Redis for session management and real-time performance.

11. Built and optimize RESTful APIs,

    ensuring efficient communication between backend services and the frontend.
12. Collaborate closely with the frontend team to integrate APIs and ensure seamless user experience.
13. Actively participate in bug fixing, performance optimization, and code reviews to maintain code quality and application stability.
14. Provid support for other projects within the organization, assisting with debugging, enhancements, and knowledge sharing.

Required Skills & Qualifications:

Bachelors or Masters in Computer Science, Artificial Intelligence, Data Science, or a related field with 3–4 years of experience with Python, focused on AI/ML development.

• Strong experience with LLMs (e.g., GPT, LLaMA, Claude, Mistral) and prompt engineering.
• Hands-on experience with LangChain, Haystack, Hugging Face, or similar libraries for building RAG-based systems.
• Familiarity with vector databases like FAISS, Pinecone, Weaviate, or Qdrant.
• Proficiency in NLP concepts such as tokenization, embeddings, named entity recognition, and summarization.
• Experience with data processing libraries (Pandas, NumPy) and ML frameworks (PyTorch, TensorFlow, scikit-learn).
• Strong understanding of RESTful API development using FastAPI, Flask, or Django.
• Familiar with Git, Docker, and model deployment best practices.

Preferred Qualifications:

• Experience fine-tuning LLMs or using adapters/LoRA for domain-specific tasks.
• Exposure to cloud services (AWS Sagemaker, Azure ML, or GCP Vertex AI).
• Knowledge of MLOps and model lifecycle management tools.
• Familiarity with search/retrieval tools (Elasticsearch, OpenSearch).
• Understanding of document ingestion pipelines and OCR/NLP integration.

Benefits:

• Competitive compensation package
• Remote work flexibility