Who are we looking for?
We are seeking a talented Python Fullstack Developer to design, develop, and deploy advanced generative AI models and solutions. The ideal candidate will have strong experience with large language models, MLOps, and end-to-end AI system implementation to drive innovation and scalability.
Key Responsibilities:
Design, develop, and deploy scalable full stack AI applications using Python and modern frontend technologies
Integrate and customize AI/ML models using frameworks such as Langsmith, Langraph, Langchain, Llama Index, and Ragas.
Develop backend services, FAstAPIs, FLASK, etc to support AI workflows and applications.
Build and maintain human-in-the-loop systems to facilitate model feedback, validation, and refinement.
Implement, and maintain enterprise knowledge graphs using graph databases (e.g., Neo4j, Amazon Neptune, GraphDB) and semantic standards (e.g., RDF, OWL, SPARQL).
Integrate AI/ML with Knowledge Graphs: Develop and apply graph-based machine learning techniques, such as Graph Neural Networks (GNNs), link prediction, and node embedding, to solve complex business problems.
Implement MLOps best practices for continuous integration, deployment, and monitoring of AI applications.
Ensure robust testing, documentation, and maintenance of AI solutions.
Collaborate closely with data scientists, ML engineers, and product teams to optimize AI model performance and usability.
Stay abreast of the latest developments in AI/ML frameworks and MLOps tools.
Required Skills & Qualifications:
Proficient in Python programming with experience in fullstack development (backend and frontend)
Hands-on experience in AI/ML development and deploying AI applications using prebuilt models.
Practical knowledge of MLOps frameworks and tools including Langsmith, Langraph, Langchain, Llama Index, and Ragas.
Experience in designing and implementing human-in-the-loop AI systems.
Experience with database technologies (SQL and NoSQL) and cloud platforms (AWS, Azure, Google Cloud Platform)
Experience with cloud AI/ML APIs and services
Familiarity with RESTful APIs, microservices, and containerization technologies (Docker, Kubernetes).
Experience with frontend technologies like ReactJS, Angular, or Vue.js
Strong problem-solving skills and ability to work in a fast-paced, collaborative environment.
Good-to-Have Skills:
Contributions to research in AI/ML, including published papers and conference presentations.
EDUCATION QUALIFICATION
Bachelor''s degree in Computer Science, Information Technology, or related field (Master''s degree preferred).
Certification:
Cloud development certification (AWS)
AI/ML certification(AWS)
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