AI Engineer

Location: Bengaluru, India

Experience: 4–8 years

Employment Type: Full-time / Permanent

We are looking for a highly skilled AI Engineer to design, develop, and deploy AI/ML and LLM-based solutions leveraging modern frameworks, GPU acceleration, and cloud environments. The ideal candidate should have hands-on experience with deep learning, Retrieval-Augmented Generation (RAG) pipelines, GitHub Copilot-assisted development, and model deployment on AWS, Azure, or GCP.

• Design, train, and fine-tune machine learning and deep learning models using TensorFlow, PyTorch, and scikit-learn.
• Develop and optimize LLM-based solutions for NLP, chatbots, and document understanding tasks.
• Build and maintain RAG (Retrieval-Augmented Generation) pipelines integrating vector databases, embeddings, and LLMs.
• Utilize GitHub Copilot and modern AI-assisted tools to accelerate model and code development.
• Work with GPU environments to optimize training performance and scalability.
• Deploy AI models as scalable APIs or services on cloud platforms (AWS Sagemaker, Azure ML, GCP Vertex AI, etc.).
• Implement MLOps best practices for versioning, CI/CD, and model monitoring.
• Collaborate with product, data, and DevOps teams to translate business needs into intelligent AI solutions.
• Stay updated with emerging trends in generative AI, transformer architectures, and cloud-based ML infrastructure.

• 4+ years of hands-on experience in AI / ML / Deep Learning engineering.
• Strong programming skills in Python and experience using Git / GitHub workflows.
• Proficiency in TensorFlow, PyTorch, and scikit-learn.
• Experience developing and deploying LLMs (e.g., GPT, LLaMA, Falcon, Mistral).
• Good understanding of RAG architectures, embeddings, and vector databases (FAISS, Pinecone, Weaviate, Chroma).
• Hands-on experience with GPU-based model training (NVIDIA CUDA / CuDNN).
• Exposure to cloud-based AI platforms – AWS Sagemaker, Azure ML, or GCP Vertex AI.
• Understanding of MLOps, Docker, Kubernetes, and CI/CD pipelines for ML.
• Strong analytical and problem-solving skills with attention to scalability and performance.

• Experience with LangChain, LlamaIndex, or OpenAI API / Azure OpenAI Service.
• Familiarity with GitHub Copilot Enterprise or similar AI coding assistants.
• Experience with prompt engineering and fine-tuning custom LLMs.
• Knowledge of data labeling, model evaluation, and experiment tracking (Weights & Biases, MLflow).
• Contributions to open-source AI projects or research publications.