Gen AI Engineer

Job Description:

Role: Gen AI / Machine Learning Engineer

Exp: 5+ Years

Location: Bangalore,Hyderabad

We are seeking a skilled Gen AI / Machine Learning Engineer with hands-on experience in Artificial Intelligence, Deep Learning, and Generative AI solutions. The ideal candidate should have at least 2+ years of experience building AI/ML models and working with Large Language Models (LLMs), RAG architectures, and cloud-based AI platforms.

You will be responsible for designing, developing, and deploying scalable AI-driven applications, including multimodal and transformer-based systems.

Key Responsibilities

AI & Machine Learning

• Design, develop, and deploy Machine Learning and Deep Learning models.
• Work on Computer Vision and NLP-based AI systems.
• Build end-to-end ML pipelines including data preprocessing, model training, evaluation, and deployment.
• Optimize models for performance, scalability, and accuracy.

Generative AI

• Implement Generative AI solutions using Large Language Models (LLMs).
• Design and develop RAG (Retrieval-Augmented Generation) architectures.
• Work with transformer-based and diffuser-based models such as BERT, GPT, T5, LLaMA, and Stable Diffusion.
• Develop prompt engineering strategies, including context-based prompts.
• Implement multimodal AI use cases (text, image, etc.).
• Work with open-source models from Hugging Face and related ecosystems.
• Use frameworks such as LangChain and LangGraph for orchestration.
• Design and integrate Vector Databases for embedding storage, indexing, and retrieval (e.g., Pinecone, FAISS, Weaviate, Chroma).

Cloud & Deployment

• Develop and deploy AI solutions on cloud platforms such as AWS SageMaker, Azure OpenAI, Google Cloud Vertex AI, or IBM WatsonX.
• Implement CI/CD pipelines for ML deployment.
• Ensure scalability, monitoring, and performance tuning of deployed AI systems.

Required Skills & Qualifications

Technical Skills

• 2+ years of experience in AI/ML, Deep Learning, or Computer Vision.
• Strong knowledge of Python and ML libraries (TensorFlow, PyTorch, Scikit-learn).
• Hands-on experience with LLMs and Generative AI frameworks.
• Experience with RAG architecture and embedding-based retrieval systems.
• Knowledge of Vector Databases and embedding techniques.
• Strong understanding of transformer architectures.
• Familiarity with model fine-tuning and inference optimization.

Cloud & DevOps

• Experience with at least one cloud AI platform (AWS SageMaker / Azure OpenAI / GCP Vertex AI / IBM WatsonX).
• Experience in API development and model serving.
• Understanding of MLOps concepts and deployment best practices.