AI/ML Engineer

Brief DescriptionCONTACT : +917293063429 Job Summary: We are seeking a highly skilled and innovative AI/ML Engineer with deep experience in Large Language Models (LLMs), Generative AI, Retrieval-Augmented Generation (RAG), and multimodal AI involving audio and video processing. The ideal candidate will have hands-on experience building and integrating cutting-edge AI solutions, fine-tuning open-source and proprietary models, and deploying them into production environments.

Key Responsibilities:

Develop and deploy solutions using LLMs (GPT, LLaMA, Mistral, Claude, etc.) for real-world applications

Implement and optimize RAG pipelines combining vector databases (e.g., Pinecone, Weaviate, FAISS) with LLMs

Fine-tune transformer-based models using Hugging Face, LoRA, QLoRA, PEFT, or similar frameworks

Work with generative AI models for text, image, audio, and video generation (e.g., Stable Diffusion, Whisper, AudioLM, DreamBooth, SDXL, etc.)

Design and integrate multimodal systems that can process and generate content across different formats

Deploy models using ONNX, TorchServe, Triton, or custom APIs

Collaborate with DevOps and MLOps teams for model versioning, deployment, and monitoring

Research, prototype, and implement the latest advancements in generative AI and foundation models

Ensure ethical AI practices, model alignment, and bias mitigation

Optimize models for performance, latency, and resource efficiency

Required Skills & Qualifications:

3+ years of hands-on experience in AI/ML engineering

Proficient with Python, PyTorch, TensorFlow, and ML libraries (e.g., Hugging Face Transformers, LangChain, OpenAI, etc.)

Strong understanding of LLMs, tokenization, attention mechanisms, and transformer architectures

Experience with fine-tuning, prompt engineering, and in-context learning

Knowledge of vector databases, embeddings, and RAG-based architectures

Familiarity with cloud platforms (AWS/GCP/Azure) and scalable AI infrastructure

Experience working with Docker, Kubernetes, and GPU optimization

Solid grasp of audio and video processing models

Passion for innovation and staying updated with the latest research and trends

Nice to Have:

Experience with AutoGPT, Agentic AI systems, or LangGraph

Knowledge of RLHF, alignment training, and custom dataset curation

Exposure to MLOps tools like MLflow, Weights & Biases, or Kubeflow

Contribution to open-source AI projects or publications in relevant areas

Preferred SkillsRequired Skills & Qualifications:

3+ years of hands-on experience in AI/ML engineering

Proficient with Python, PyTorch, TensorFlow, and ML libraries (e.g., Hugging Face Transformers, LangChain, OpenAI, etc.)

Strong understanding of LLMs, tokenization, attention mechanisms, and transformer architectures

Experience with fine-tuning, prompt engineering, and in-context learning

Knowledge of vector databases, embeddings, and RAG-based architectures

Familiarity with cloud platforms (AWS/GCP/Azure) and scalable AI infrastructure

Experience working with Docker, Kubernetes, and GPU optimization

Solid grasp of audio and video processing models

Passion for innovation and staying updated with the latest research and trends