Generative AI Application Developer

3 weeks ago

Bengaluru, Karnataka, India Zensar Technologies Full time

Position : Generative AI Application Developer

Experience : 7-16 years

Location : Bangalore, Hyderabad, and Pune, India

Notice Period : Early joiners are highly appreciated.

Job Summary :

We are seeking a highly skilled and experienced Generative AI Application Developer to architect, develop, and deploy production-grade AI systems. The ideal candidate will possess deep technical expertise in the end-to-end lifecycle of Generative AI models, with a strong focus on building scalable and robust applications. This role requires a hands-on developer who can translate complex business challenges into innovative solutions using Large Language Models (LLMs) and other generative Responsibilities : Development & Fine-Tuning :

- Design, build, and train Generative AI models and algorithms using deep learning techniques.

- Implement and fine-tune Large Language Models (LLMs) using custom datasets to meet specific business requirements.

- Apply techniques such as Retrieval-Augmented Generation (RAG) and prompt engineering to enhance model performance and reduce Engineering & Preparation :

- Architect and implement data pipelines for the ingestion, preprocessing, and transformation of large datasets.

- Manage and optimize vector databases for efficient semantic search and information Development & Integration :

- Develop robust, scalable applications that integrate Generative AI models using APIs and microservices.

- Build prototypes and demonstrate proof-of-concepts (POCs) to technical and business stakeholders.

- Ensure seamless integration of AI applications with existing enterprise & MLOps :

- Deploy and manage AI models in production environments using MLOps principles.

- Implement CI/CD pipelines for continuous integration and deployment of machine learning code.

- Monitor model performance, latency, and resource utilization & Innovation :

- Stay current with the latest advancements in Generative AI, deep learning, and transformer architectures.

- Evaluate and experiment with new models, frameworks, and tools to drive Skills : :

- Expert-level proficiency in Python.

- Strong experience with software engineering fundamentals, including object-oriented programming, data structures, and Expertise :

- Deep understanding of deep learning frameworks such as PyTorch or TensorFlow.

- Hands-on experience with Generative AI models (e.g., GANs, VAEs) and architectures (e.g., Transformers, diffusion models).

- Proven experience with Large Language Models (LLMs), fine-tuning, RAG, and prompt & Cloud :

- Strong experience with cloud platforms for AI/ML (AWS SageMaker, Azure ML, or GCP Vertex AI).

- Familiarity with MLOps tools like MLflow, Kubeflow, or DVC.

- Experience with containerization technologies like & APIs :

- Experience with vector databases such as Pinecone, ChromaDB, or FAISS.

- Proficient in SQL and knowledge of NoSQL databases.

- Experience with building and consuming RESTful APIs and :

- Hands-on experience with key libraries such as Hugging Face Transformers, LangChain, or Engineering Practices : - Strong knowledge of version control systems, especially Skills : - Experience developing SaaS products or consumer-facing applications powered by Generative AI.

- Knowledge of specific cloud-native services like AWS Bedrock, Azure OpenAI Service, or GCP's Vertex AI Model Garden.

- Familiarity with other programming languages such as Java or C++ for high-performance computing.

- Experience with UI/UX frameworks (React, Angular) to build user interfaces for AI applications.

- Contributions to open-source projects in the AI or machine learning community.

- Relevant cloud certifications (AWS Certified Machine Learning Specialty).

(ref:hirist.tech)

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