We are seeking a highly skilled Senior AI/ML Engineer with deep expertise in Artificial Intelligence, Machine Learning, and Large Language Models (LLMs). The ideal candidate will have hands-on experience in building, fine-tuning, and deploying production-grade AI models with a focus on Generative AI, MLOps, and scalable real-time inference systems. Key Responsibilities; Design, develop, and deploy AI/ML models with a strong emphasis on applied problem-solving. Work on Generative AI, LLMs, RAG pipelines, and prompt engineering to build next-gen AI solutions. Implement MLOps automation for end-to-end model lifecycle management using tools like MLflow, Kubeflow, or SageMaker. Optimize training and inference workflows leveraging NVIDIA GPU tools (CUDA, TensorRT, Triton Inference Server). Collaborate with cross-functional teams to design real-time AI pipelines and scalable deployment architectures . Stay ahead of industry trends, research advancements, and best practices in AI/ML and Generative AI. Must-Have Skills (5+ Years Relevant Experience) Strong applied expertise in Artificial Intelligence & Machine Learning . Proven experience in Generative AI & LLMs fine-tuning, retrieval-augmented generation (RAG), and prompt engineering. MLOps proficiency automation of model training, deployment, and monitoring using MLflow, Kubeflow, SageMaker, or similar tools. Python – Expert level , with hands-on experience in PyTorch, TensorFlow, Hugging Face, Scikit-learn, etc. Experience with NVIDIA GPU frameworks and tools – CUDA, TensorRT, Triton Inference Server. Strong knowledge of model deployment, serving, and real-time AI pipelines . Good to Have Experience with JavaScript/TypeScript for AI/ML integration with front-end systems. Familiarity with modern AI/ML tools: LangChain, LlamaIndex, Vector Databases (FAISS, Pinecone, Weaviate). Cloud ML platforms – AWS, GCP, Azure ML . Knowledge of Docker, Kubernetes, and RESTful APIs for containerized deployments. Eligibility Minimum 5+ years of relevant, hands-on AI/ML/LLM experience (not just research, but applied/production). Willingness to work from Hyderabad (relocation required if not currently based in Hyderabad). Passionate about building impactful, production-grade AI systems that scale.
We are seeking a highly skilled Senior AI/ML Engineer with deep expertise in Artificial Intelligence, Machine Learning, and Large Language Models (LLMs). The ideal candidate will have hands-on experience in building, fine-tuning, and deploying production-grade AI models with a focus on Generative AI, MLOps, and scalable real-time inference systems. Key Responsibilities; Design, develop, and deploy AI/ML models with a strong emphasis on applied problem-solving. Work on Generative AI, LLMs, RAG pipelines, and prompt engineering to build next-gen AI solutions. Implement MLOps automation for end-to-end model lifecycle management using tools like MLflow, Kubeflow, or SageMaker. Optimize training and inference workflows leveraging NVIDIA GPU tools (CUDA, TensorRT, Triton Inference Server). Collaborate with cross-functional teams to design real-time AI pipelines and scalable deployment architectures . Stay ahead of industry trends, research advancements, and best practices in AI/ML and Generative AI. Must-Have Skills (8+ Years Relevant Experience) Strong applied expertise in Artificial Intelligence & Machine Learning . Proven experience in Generative AI & LLMs fine-tuning, retrieval-augmented generation (RAG), and prompt engineering. MLOps proficiency automation of model training, deployment, and monitoring using MLflow, Kubeflow, SageMaker, or similar tools. Python Expert level , with hands-on experience in PyTorch, TensorFlow, Hugging Face, Scikit-learn, etc. Experience with NVIDIA GPU frameworks and tools – CUDA, TensorRT, Triton Inference Server. Strong knowledge of model deployment, serving, and real-time AI pipelines . Good to Have Experience with JavaScript/TypeScript for AI/ML integration with front-end systems. Familiarity with modern AI/ML tools: LangChain, LlamaIndex, Vector Databases (FAISS, Pinecone, Weaviate). Cloud ML platforms – AWS, GCP, Azure ML . Knowledge of Docker, Kubernetes, and RESTful APIs for containerized deployments. Eligibility Minimum 8 + years of relevant, hands-on AI/ML/LLM experience (not just research, but applied/production). Willingness to work from Hyderabad (relocation required if not currently based in Hyderabad). Passionate about building impactful, production-grade AI systems that scale.