Artificial Intelligence Engineer

Position: AI ML Engineer Location: Indiranagar, bengaluru Working Days: 5 days Work Timings: 10am -7pm Experience Required: 2 -6 years Client: Leading B2B Fintech Startup Salary: 25 LPA - 40 LPA Job Description : Build with LLMs & GenAI : • Fine-tune and deploy Large Language Models (LLMs) like GPT, BERT, etc., for core AI features across the product • Develop and optimize Generative AI capabilities — diffusion models, LoRA, or similar frameworks • Continuously improve performance using prompt engineering, retrieval-augmented generation (RAG), and user feedback Deploy AI Workflows : • Build scalable, production-ready AI workflows and pipelines using APIs, microservices, and vector databases • Translate prototypes into stable product features in collaboration with product and backend teams • Integrate AI systems into real-time and batch data processing layers Infrastructure & Performance • Work with cloud GPU environments (AWS/GCP/Azure) to train, run, and monitor LLM-based systems : • Optimize inference latency and throughput for high-scale use cases Requirements for the Role : • 2–6 years of experience in AI/ML Engineering • Strong Python skills with experience in frameworks like PyTorch or TensorFlow • Proven hands-on experience with LLMs, prompt engineering, or Generative AI models • Experience deploying models to production in a cloud environment (AWS/GCP/Azure) • Comfortable with tools like HuggingFace, LangChain, or similar open-source stacks Core Expertise • Experience working with transformer-based LLMs (e.g., GPT, BERT, Falcon, LLaMA). • Strong foundation in ML algorithms, deep learning, and model deployment. • Proven track record in Generative AI and MLOps. Technical Stack : • Languages: Python (must-have), bonus for Golang or Node.js. • Frameworks: TensorFlow, PyTorch, Hugging Face. • Infra & DevOps: AWS/GCP/Azure, Docker, Kubernetes. • Pipelines: MLflow, Kubeflow, Airflow.