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 Lang Chain and Lang Graph 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 Sage Maker, Azure OpenAI, Google Cloud Vertex AI, or IBM Watson

X.
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 (Tensor Flow, 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 & Dev Ops

Experience with at least one cloud AI platform (AWS Sage Maker / Azure OpenAI / GCP Vertex AI / IBM Watson

X).
Experience in API development and model serving.
Understanding of MLOps concepts and deployment best practices.