Lead the development of robust, high-performance web and generative AI applications.
Build and deploy GenAI solutions leveraging Retrieval-Augmented Generation (RAG) pipelines for intelligent document querying, summarization, and semantic search.
Extract, structure, and process data from complex documents (PDFs, images, scanned forms) using integrated OCR engines (e.g., Tesseract, PaddleOCR) and vision-language models.
Develop RAG-based GenAI applications using tools like LangChain and LlamaIndex, and work with vector databases (e.g., FAISS, Weaviate) for efficient embedding-based retrieval.
Integrate OCR, LLMs, and vector search into business applications to automate the extraction, understanding, and processing of unstructured content.
Design, train, and optimize both Small Language Models (SLMs) and Large Language Models (LLMs) for domain-specific applications, ensuring efficiency and high performance.
Develop scalable training pipelines leveraging methods such as supervised fine-tuning, reinforcement learning from human feedback (RLHF), prompt tuning, parameter-efficient fine-tuning (e.g., LoRA, adapters), and knowledge distillation.
Fine-tune, evaluate, and deploy language models using advanced techniques like quantization, continual learning, and model distillation to meet evolving business requirements.
Analyze and monitor model outputs for quality, bias, and safety, iterating to improve accuracy and model alignment with user and business needs.
Architect, design, and implement scalable and secure solutions aligned with business objectives.
Mentor and guide a team of developers, fostering a culture of continuous learning and improvement.
Design and maintain APIs, including RESTful and GraphQL interfaces, ensuring seamless data exchange with third-party services.
Implement and maintain CI / CD pipelines, utilizing automation tools for seamless deployment.
Collaborate with cross-functional teams, including DevOps, Security, Data Science, and Product Management.
Optimize application performance by efficiently managing resources, implementing load balancing, and optimizing queries.
Ensure compliance with industry security standards such as GDPR.
Stay updated with emerging technologies, especially in Generative AI, Machine Learning, cloud computing, and microservices architecture.
Required Qualifications :
Bachelor’s or master’s degree in computer science, Engineering, or a related field.
6+ years of hands-on experience in AI & Python development, with expertise in Django, Flask, or FastAPI.
Ability to design and build end-to-end applications and API integrations
Proven experience with large language models (LLMs) and AI model development
Experience with developing retrieval-augmented generation (RAG).
Experience with GenAI tools like Langchain, LlamaIndex, LangGraph, and open-source Vector DBs.
Exposure to prompt engineering principles and techniques like chain of thought, in-context learning, tree of thought, etc.
Exposure to SLMs.
Experience with supervised fine-tuning, reinforcement learning from human feedback (RLHF), prompt tuning, parameter-efficient fine-tuning (e.g., LoRA, adapters), and knowledge distillation.
Experience with relational databases such as MS SQL Server, PostgreSQL, and MySQL.
Expertise in DevOps practices, including Docker, Kubernetes, and CI / CD tools like GitHub Actions.
Deep understanding of microservices architecture and distributed computing principles.
Strong knowledge of security best practices in software development.
Familiarity with data analytics and visualization tools such as Snowflake, Looker, Tableau, or Power BI.
Excellent problem-solving skills and the ability to work independently and within a team.
Strong communication and stakeholder management skills.
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Lead Engineer Python • hyderabad, India
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